Methods, systems, apparatus, and tangible non-transitory carrier media encoded with one or more computer programs for classifying an input text block into a sequence of one or more classes in a multi-level hierarchical classification taxonomy. In accordance with particular embodiments, a source sequence of inputs corresponding to the input text block is processed, one at a time per time step, with an encoder recurrent neural network (RNN) to generate a respective encoder hidden state for each input, and the respective encoder hidden states are processed, one at a time per time step, with a decoder RNN to produce a sequence of outputs representing a directed classification path in a multi-level hierarchical classification taxonomy for the input text block.
Example methods, apparatus, and articles of manufacture to classify labels based on images using artificial intelligence are disclosed. An example apparatus includes a regional proposal network to determine a first bounding box for a first region of interest in a first input image of a product; and determine a second bounding box for a second region of interest in a second input image of the product; a neural network to: generate a first classification for a first label in the first input image using the first bounding box; and generate a second classification for a second label in the second input image using the second bounding box; a comparator to determine that the first input image and the second input image correspond to a same product; and a report generator to link the first classification and the second classification to the product.
G06T 3/40 - Scaling of a whole image or part thereof
G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/771 - Feature selection, e.g. selecting representative features from a multi-dimensional feature space
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
3.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DETERMINE PRODUCT SIMILARITY SCORES
Methods, systems, articles of manufacture and apparatus to determine product similarity scores are disclosed. An example apparatus includes calculation set generating circuitry to identify a set of candidate comparison items based on primary characteristics corresponding to the a focus item, and generate a calculation set of items from the set of candidate comparison items based on secondary characteristics corresponding to market performance, and weight calculating circuitry to calculate primary characteristic scores corresponding to the focus item, the primary characteristic scores based on a uniqueness between the primary characteristics corresponding to the focus item and primary characteristics corresponding to the calculation set of items.
An example system includes a first headset including first sensor to gather first user data from a first subject during exposure to media, the first user data including at least one of psychophysiological data or physiological data; and a first processor to generate first data indicative of an emotional response of the first subject based on the first user data. The example system includes a second headset including a second sensor to gather second user data from the second subject during exposure to the media, the second user data including at least one of psychophysiological data or physiological data; a second processor to generate second data indicative of an emotional response of the second subject based on the second user data and synchronize the second data with the first data to generate synchronized response data; and a second transmitter to transmit the synchronized response data to a central processor.
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
A61B 5/16 - Devices for psychotechnics; Testing reaction times
A61B 5/377 - Electroencephalography [EEG] using evoked responses
H04N 7/16 - Analogue secrecy systems; Analogue subscription systems
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/475 - End-user interface for inputting end-user data, e.g. PIN [Personal Identification Number] or preference data
5.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO TAG SEGMENTS IN A DOCUMENT
Methods, apparatus, systems, and articles of manufacture are disclosed to tag segments in a document. An example apparatus includes processor circuitry to execute machine readable instructions to generate node embeddings for nodes of a graph, the node embeddings based on features extracted from text segments detected in a document, the text segments to be represented by the nodes of the graph; sample edges corresponding to the nodes to generate the graph; generate first updated node embeddings by passing the node embeddings and the graph through layers of a graph neural network, the first updated embeddings corresponding to the node embeddings augmented with neighbor information; generate second updated node embeddings by passing the first updated embeddings through layers of a recurrent neural network, the second updated embeddings corresponding to the first updated node embeddings augmented with sequential information; and classify the text segments based on the second updated node embeddings.
Systems, apparatus, articles of manufacture, and methods are disclosed to detect promotion events. An apparatus includes interface circuitry to obtain aligned sales data corresponding to products, the products corresponding to a market and a category; computer readable instructions; and programmable circuitry to instantiate event detection circuitry to: identify product-level promotions based on the aligned sales data and corresponding baseline data for the products; and group ones of the product-level promotions to identify promotion events; and expansion circuitry to determine uplift factors for different promotion characteristics based on the market and the category; and apply the uplift factors to the product-level promotions and the promotion events to identify incremental sales.
Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example apparatus for clustering vertices, the apparatus comprises machine-readable memory, instructions, and processor circuitry to execute the machine-readable instructions to calculate a centroid corresponding to coordinates, calculate distances for respective ones of the coordinates relative to the centroid, calculate differences between the distances, determine whether ones of the differences satisfy a set of thresholds, in response to determining that ones of the differences satisfy the set of thresholds, calculate bearing angles for ones of the coordinates, determine an efficiency metric associated with respective ones of the bearing angles, sort each of the bearing angles based on the associated efficiency metric, and form coordinate clusters based on the sorted bearing angles.
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
G06F 7/24 - Sorting, i.e. extracting data from one or more carriers, re-arranging the data in numerical or other ordered sequence, and re-recording the sorted data on the original carrier or on a different carrier or set of carriers
8.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO DETERMINE RELATED CONTENT IN A DOCUMENT
Methods, apparatus, systems, and articles of manufacture are disclosed that determine related content. An example apparatus includes processor circuitry to generate a segment-level graph by sampling segment-level edges among segment nodes representing text segments, the segment-level graph including segment node embeddings representing features of the segment nodes; cluster the text segments to form entities by applying a first GAN based model to the segment-level graph to update the segment node embeddings; generate a multi-level graph by (a) generating an entity-level graph including hypernodes representing the entities and sampled entity edges connecting ones of the hypernodes, and (b) connecting the segment nodes to respective ones of the hypernodes using relation edges; generate hypernode embeddings by propagating the updated segment node embeddings using a relation graph; and cluster the entities by product by applying a second GAN based model to the multi-level graph, the multi-level graph to generate updated hypernode embeddings.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
9.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO IMPROVE ISOTONIC REGRESSION
Methods, apparatus, systems, and articles of manufacture are disclosed to improve isotonic regression, the methods, apparatus, systems, and articles of manufacture comprising: interface circuitry; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: analyze a set of data points to generate a subset of data points that violate a trend rule; average the subset of data points to establish a pooled data point value; and adjust the pooled data point value to satisfy an upper boundary and a lower boundary corresponding to respective subset data point interval bound information to generate a minimizer.
Methods, apparatus, systems, and articles of manufacture are disclosed for determining new product metrics using cross-channel analytics. An example apparatus includes processor circuitry to at least compare first products data associated with a first channel and second products data associated with a second channel to identify a product of interest corresponding to a product present in the first products data and not in the second products data, and third products corresponding to products present in both the first products data and the second products data, cluster the third products based on at least one metric to generate product clusters, for ones of the product clusters in the cluster output, calculate a ratio of a performance metric of the third products, and determine a value of a performance metric for the product of interest based on the first products data and a ratio of the performance metric.
Methods, apparatus, systems, and articles of manufacture are disclosed that detect lines in a document. An example apparatus includes at least one memory; machine readable instructions; and processor circuitry to at least one of instantiate or execute the machine readable instructions to: generate feature embeddings for text segments detected in a document image, the segments associated with respective bounding boxes, wherein the segments are to be represented by nodes in a graph; identify candidate edges between ones of the segments; pass the feature embeddings through graph attention layers (GAT) to update the feature embeddings with information from neighbor nodes; generate an adjacency matrix for the document image by determining confidence scores for the edges; and cluster the nodes based on the adjacency matrix to group ones of the nodes that belong to a same line.
Methods, apparatus, systems, and articles of manufacture are disclosed to regress independent and dependent variable data. An example apparatus to generate movement values for a regression model includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to calculate period average sales values for ones of stores associated with (a) a store group of interest, (b) a category of interest and (c) ones of periods of interest, the period average sales values based on a number of the ones of the stores. The example processor circuitry also at least one of instantiates or executes the machine readable instructions to calculate period average stock values for the ones of the stores associated with (a) the store group of interest, (b) the category of interest and (c) the ones of the periods of interest, the period average stock values based on the number of ones of the stores, calculate overall average sales values based on the period average sales values corresponding to all of the ones of the periods of interest, calculate overall average stock values based on the period average stock values corresponding to all of the ones of the periods of interest, and prevent random effects corresponding to stock input data used in the regression model by calculating sales movement values based on a difference between the period average sales values and the overall sales values, and calculating stock movement values based on a difference between the period average stock values and the overall average stock values.
Methods, apparatus, systems, and articles of manufacture are disclosed to improve model training efficiency comprising block circuitry to: generate a first blocking corresponding to first ones of first data samples retrieved from a first data source, the first ones of the first data samples including a first heuristic; and generate a second blocking corresponding to second ones of the first data samples that include a second heuristic; match circuitry to: retrieve a second data sample from a second data source and determine a match of the first blocking or the second blocking; and assign respective ones of the first data samples from the match one of a first designation type or a second designation type; and batch circuitry to: combine the first designation type and the second designation type into a machine learning input batch.
Methods, apparatus, systems, and articles of manufacture are disclosed to improve modeling efficiency identify a first quantity of modes corresponding to a task, apply a model to the first quantity of modes to determine a first contributory effect corresponding to the task, select a first portion of the first quantity of modes to exclude to generate a second quantity of modes corresponding to the task, apply the model to the second quantity of modes to determine a second contributory effect corresponding to the task, and cause a trigger response based on a difference value between the first contributory effect and the second contributory effect.
Methods, apparatus, systems, and articles of manufacture are disclosed to decode receipts based on neural graph architecture. An apparatus includes interface circuitry to obtain an image of a document; machine readable instructions; and programmable circuitry to execute the machine readable instructions to at least generate nodes for a feature graph based on features extracted from text boxes, the nodes including polar coordinates indicative of angular positions of the text boxes; pass the feature graph through a graph neural network to generate an adjacency matrix; and identify text lines in the image of the document by clustering the nodes by line based on the adjacency matrix.
G06F 18/213 - Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
G06F 7/24 - Sorting, i.e. extracting data from one or more carriers, re-arranging the data in numerical or other ordered sequence, and re-recording the sorted data on the original carrier or on a different carrier or set of carriers
Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium is disclosed comprising instructions that, when executed, cause a machine to at least generate a baseline product hierarchy using product information, calculate categorical impact values for products in the baseline product hierarchy, calculate an average impact value for the baseline product hierarchy using the calculated categorical impact values, calculate a first weighting factor for respective ones of the products based on a comparison between the categorical impact values and the average impact value, calculate a second weighting factor associated with respective ones of the products in the baseline product hierarchy based on sales data, and generate final weighted categorical impact values based on (a) the first weighting factors, (b) the second weighting factors and (c) the categorical impact values corresponding to the respective ones of the products.
Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
G06T 11/60 - Editing figures and text; Combining figures or text
18.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO IMPROVE TAGGING ACCURACY
Methods, apparatus, systems, and articles of manufacture are disclosed to improve tagging accuracy. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to at least search a first row of a document to identify a first row that includes a first type of entity, search the first row of the document to identify a second type of entity that is missing, search the first row of the document to identify a first integer value, and associate the first row with a product corresponding to the first integer value.
Example headsets and electrodes are described herein. Example electrode units described herein include a housing having a cavity defined by an opening in a side of the housing and an electrode. In some such examples, the electrode includes a ring disposed in the opening and an arm, where the arm has a first portion extending outward from the opening away from the housing and a second portion extending from an end of the first portion toward the housing and into the cavity, and the first and second portions connect at a bend.
Methods, apparatus, systems, and articles of manufacture are disclosed for decoding images. An example apparatus to decode an image comprises interface circuitry to receive an image of a purchase document, and processor circuitry to execute the machine readable instructions to extract text from the image of the purchase document, the image of the purchase document to memorialize a transaction that includes at least one product; determine a type of the purchase document to which the image corresponds; apply one of a first pipeline or a second pipeline to the image of the purchase document based on the type of the purchase document; obtain purchase facts corresponding to a respective one of the at least one product memorialized in the image of the purchase document; and map the obtained purchase facts against a products database to identify the at least one product memorialized in the image of the purchase document.
Methods, apparatus, systems, and articles of manufacture are disclosed for processing an image using visual and textual information. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to detect regions of interest corresponding to a product promotion of an input digital leaflet, extract textual features from the product promotion by applying an optical character recognition (OCR) algorithm to the product promotion and associating output text data with corresponding ones of the regions of interest, determine a search attribute corresponding to the product promotion, generate a first dataset of candidate products corresponding to the product in the product promotion by comparing the search attribute against a second dataset of products, and select a product from the first dataset of candidate products to associate with the product promotion, the product selected based on a match determination.
Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least improve region of interest detection efficiency by converting pixels of an input receipt image from a first format to a second format, generate a binary representation of the input receipt image based on the converted pixels, the binary representation of the input receipt image corresponding to saturation values for respective ones of the converted pixels, calculate mirror data from the binary representation of the input receipt image, and cluster the binary representation of the input receipt image to identify a first set of candidate regions of interest, the candidate regions of interest characterized by portions of the binary representation of the input receipt image having saturation values that satisfy a threshold value.
Methods, systems, articles of manufacture, and apparatus to recalibrate confidences for image classification are disclosed. An example apparatus to classify an image includes an image crop detector to detect a first image crop from the image, the first image crop corresponding to a first object, a grouping controller to select a second image crop corresponding to a second object at a location of the first object, a prediction generator to, in response to executing a trained model, determine a label corresponding to the first object and a confidence level associated with the label, and a confidence recalibrator to recalibrate the confidence level based on a probability of the first object having a first attribute based on the second object having a second attribute, the confidence level recalibrated to increase an accuracy of the image classification.
G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
G06F 18/214 - Generating training patterns; Bootstrap methods, e.g. bagging or boosting
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
24.
METHODS, SYSTEMS, APPARATUS AND ARTICLES OF MANUFACTURE TO MODEL eCOMMERCE SALES
Methods, apparatus, systems and articles of manufacture methods, systems, apparatus and articles of manufacture to model ecommerce sales are disclosed. A system to model to eCommerce sales includes a trend identifier to compute commerce metric differences corresponding to products, the commerce metric differences based on first commerce metrics scraped at a first time and second commerce metrics scraped at a second time, a splitter to split the commerce metric differences into a first portion of the commerce metric differences corresponding to a first dataset of eCommerce cooperators, and into a second portion of the commerce metric differences corresponding to a second dataset of eCommerce non-cooperators, a machine learning engine to infer sales data by estimating eCommerce non-cooperators sales based on the second portion of the commerce metric differences, and a sales allocator to estimate sales missing from collected sales data based on the estimate eCommerce non-cooperators sales.
Methods, systems, articles of manufacture and apparatus are disclosed to label text on images. An example apparatus includes colorizer circuitry to apply color to text boxes corresponding to optical character recognition (OCR) data associated with an image, OCR manager circuitry to render an OCR text prompt associated with the OCR data, the OCR text prompt to be rendered proximate to respective ones of the text boxes, the OCR text prompt to display a text portion of the OCR data, and edit circuitry to (a) render an interface in response to selection of the OCR text prompt, the interface populated with the text portion of the OCR data, and (b) in response to an overwrite input to the interface, update the text portion of the OCR data in a memory corresponding to the image.
Methods, apparatus, systems, and articles of manufacture are disclosed that decode purchase data using an image. An example apparatus includes processor circuitry to execute machine readable instructions to at least crop an image of a receipt based on detected regions of interest, apply a first mask to a first cropped image to generate first bounding boxes corresponding to rows of the receipt, apply a second mask to a second cropped image to generate second bounding boxes corresponding to columns of the receipt, generate a structure of the receipt by mapping words detected by an optical character recognition engine to corresponding first bounding boxes and second bounding boxes based on a mapping criterion, classify the second bounding boxes by identifying an expression of interest in ones of the second bounding boxes, and generate purchase information by extracting text of interest from the structured receipt based on the classifications.
Methods, apparatus, systems, and articles of manufacture are disclosed to decode receipts based on neural graph architecture. An example apparatus for decoding receipts includes, vertex feature representation circuitry to extract features from optical-character-recognition (OCR) words, polar coordinate circuitry to: calculate polar coordinates of the OCR words based on respective ones of the extracted features, graph neural network circuitry to generate an adjacency matrix based on the extracted features, post-processing circuitry to traverse the adjacency matrix to generate cliques of OCR processed words, and output circuitry to generate lines of text based on the cliques of OCR processed words.
G06F 7/24 - Sorting, i.e. extracting data from one or more carriers, re-arranging the data in numerical or other ordered sequence, and re-recording the sorted data on the original carrier or on a different carrier or set of carriers
Methods, apparatus, systems, and articles of manufacture are disclosed that decode purchase data using an image. An example apparatus includes a dictionary including associated product descriptions and barcodes, interface circuitry, and processing circuitry to execute machine readable instructions to obtain purchase details and barcodes corresponding to a receipt, the purchase details including receipt product descriptions, generate a search query that includes a first receipt product description of the receipt product descriptions, a list of barcodes corresponding to the barcodes, and a store identifier associated with the receipt, execute a search against the dictionary using the search query to identify a barcode from the list of barcodes that corresponds to the first receipt product description, and in response to identifying the barcode that corresponds to the first receipt product description, associating the barcode and the first receipt product description and adding the association to the dictionary.
G06V 30/42 - Document-oriented image-based pattern recognition based on the type of document
G06V 30/414 - Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
Examples methods, apparatus/systems and articles of manufacture for auditing point-of-sale images are disclosed herein. Example methods disclosed herein include comparing a region of interest of an image displayed via a user interface with a plurality of reference product images stored in a database to identify a plurality of candidate product images from the plurality of reference product images as potential matches to a first product depicted in the image. For example, the candidate product images are associated with respective confidence levels indicating respective likelihoods of matching the first product. Disclosed example methods also include displaying, via the user interface, the candidate product images simultaneously with the image in a manner based on the respective confidence levels, and automatically selecting a first one of the candidate product images as matching the first product based on the respective confidence levels.
G06F 16/51 - Indexing; Data structures therefor; Storage structures
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
30.
Methods, systems, apparatus, and articles of manufacture for document scanning
Methods, systems, apparatus, and articles of manufacture for document scanning are disclosed. An example apparatus includes a base structured to position a mobile device, the base including an opening corresponding to a camera of the mobile device, and at least two side panels couplable to and foldable toward the base, the side panels to maintain a first distance between the base and a target document, the side panels slidable along the target document.
Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus includes processor circuitry to execute instructions to extract text from the receipt image, the text including bounding boxes; associate ones of the bounding boxes to link horizontally related fields of a the receipt image by selecting a first bounding box; identifying first horizontally aligned bounding boxes, the first horizontally aligned bounding boxes to include at least one bounding box of the bounding boxes that is horizontally aligned relative to the first bounding box; adding the first horizontally aligned bounding boxes to a word sync list; and connecting ones of the first horizontally aligned bounding boxes and the first bounding box based on at least one of an amount of the first horizontally aligned bounding boxes in the word sync list and a relationship among the first horizontally aligned bounding boxes and the first bounding box.
Methods, apparatus, systems disclosed herein include a work plan generator to generate market vehicle scores corresponding to available market vehicles, the market vehicle scores based on at least one client weight and at least one vehicle metric, and perform a comparison of the market vehicle scores associated with vehicle types to determine a first vehicle assignment and a second vehicle assignment, the first vehicle assignment associated with a first vehicle type, the second vehicle assignment associated with a second vehicle type; and generate first work plans, the first work plans corresponding to (a) a sequence of tasks and (b) a set of corresponding vehicles to execute the sequence of tasks, and a vehicle metrics generator to update vehicle metrics instructions associated with the first vehicle assignment and the second vehicle assignment to facilitate subsequent execution of second work plans, a first subset of the second work plans corresponding to first ones of the sequence of tasks executed by the first vehicle assignment and a second subset of the second work plans corresponding to second ones of the sequence of tasks executed by the second vehicle assignment.
Methods, apparatus, systems and articles of manufacture are disclosed to monitor auditing devices. An example apparatus includes a workload analyzer to obtain alert data related to a potential new product from an auditing device, and a product analyzer to identify a product within the alert data to determine if the product has been previously identified by another auditing device. In response to determining that the product has not been previously identified, the example apparatus includes an alert analyzer to cluster the alert data based on characteristics associated with an auditor profile of the auditing device, and determine a probability of transmitting the alert data to other auditing devices based on the clustered alert data. The example apparatus also includes an alert authorizer to suppress the alert data from being transmitted to the other auditing devices to reduce an amount of network resources required for subsequent processing when the probability does not satisfy a threshold.
G06Q 50/00 - Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
34.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DETERMINE HEADROOM METRICS FROM MERGED DATA SOURCES
Methods, apparatus, systems and articles of manufacture are disclosed to determine headroom. An example apparatus disclosed herein includes a data retriever to retrieve a first data set and a second data set, the first and second data sets including observations, an overlap calculator to merge respective ones of the observations to form an overlap data set, the respective ones of the observations merged based on first tier parameters, a similarity calculator to calculate similarity scores for pairs of the respective ones of the observations in the overlap data set, the similarity score based on second tier parameters, and a data joiner to associate respective ones of the similarity scores with corresponding households associated with the respective ones of the observations.
A method comprises displaying visual representations of a plurality of product alternatives each including at least one attribute variant to a respondent, receiving from the respondent an indication of a preferred one of the plurality of product alternatives, transmitting a request to the respondent to identify at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives and receiving a response from the respondent identifying at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives.
An example system includes an analyzer to identify a degree of amplitude synchrony between a first pattern in a first frequency band in first neuro-response data and a second pattern in a second frequency band in the first neuro-response data, the first neuro-response data gathered via a first modality of collection from a subject while the subject is exposed to media, and modify the degree of amplitude synchrony in response to activity in second neuro-response data, the second neuro-response data gathered via a second modality of collection from the subject while the subject is exposed to the media, the activity corresponding in time to at least a portion of the first pattern or the second pattern. The example system includes an estimator to determine an effectiveness of the media based on the modified degree of amplitude synchrony.
An example system includes an analyzer to identify first activity in first neuro-response data, the first activity generated in response to exposure of a subject to a first stimulus prior to exposure to an advertisement or entertainment; identify second activity in second neuro-response data, the second activity generated in response to re-exposure of the subject to the first stimulus after to exposure to the advertisement or entertainment; calculate a differential event related potential measurement; and calculate a differential event related power spectral perturbation. The example system includes a resonance estimator to determine a subject resonance measurement to the advertisement or the entertainment based on the differential event related potential measurement and adjust at least one of the subject resonance measurement or the differential event related potential measurement based on the differential event related power spectral perturbation to generate an adjusted subject resonance measurement.
Methods, apparatus, systems and articles of manufacture are disclosed to analyze characteristics of text of interest using a computing system. An example apparatus includes a text detector to provide text data from a first image, the first image including a first text region of interest and a second text region not of interest, a color-coding generator to generate a plurality of color-coded text-map images, the plurality of color-coded text-map images including color-coded segments with different colors, the color-coded segments corresponding to different text characteristics, and a convolutional neural network (CNN) to determine a first location in the first image as more likely to be the first text region of interest than a second location in the first image corresponding to the second text region that is not of interest based on performing a CNN analysis on the first image and the plurality of color-coded text-map images.
Methods, systems, articles of manufacture, and apparatus to recalibrate confidences for image classification are disclosed. An example apparatus to classify an image includes an image crop detector to detect a first image crop from the image, the first image crop corresponding to a first object, a grouping controller to select a second image crop corresponding to a second object at a location of the first object, a prediction generator to, in response to executing a trained model, determine a label corresponding to the first object and a confidence level associated with the label, and a confidence recalibrator to recalibrate the confidence level based on a probability of the first object having a first attribute based on the second object having a second attribute, the confidence level recalibrated to increase an accuracy of the image classification.
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
Methods, apparatus, and systems are disclosed to measure online purchasing history. An example apparatus includes a query controller to: generate a first request to a first order history page of a first retailer based on obtaining authorization to access the first order history page, and generate a second request to a second order history page of a second retailer based on obtaining authorization to access the second order history page, the first and second retailers selected based on a list of retailers, and a scrape controller to: scrape the first order history page and the second order history page, identify order characteristics based on information scraped from the first order history page and the second order history page, the order characteristics indicative of an online purchasing behavior corresponding to the first retailer and the second retailer, and store order characteristics in memory to provide to a central facility.
Methods, systems, apparatus and articles of manufacture are disclosed herein to apply a regularization loss in machine learning models. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to identify at least one neural network filter with filter norm values below a filter norm threshold, the filter norm values corresponding to filter functionality, a higher level of filter functionality corresponding to decreased filter death, correct the filter norm values by applying a survival loss function, the survival loss function including one or more hyperparameters, reduce filter death by adjusting the one or more hyperparameters used to define a minimum filter norm for identification of filter functionality, the adjustment based on neural network filter performance, a functional filter to return non-zero parameter values indicating reduction of filter death, and train the neural network for use in continual learning with the at least one neural network filter corrected using the survival loss function.
Methods, apparatus, systems and articles of manufacture are disclosed to control market strategy adjustments. An example apparatus includes a target principle generator to determine a target principle of a product based on at least one lever, the at least one lever indicative of an adjustable parameter corresponding to the product, an execution analyzer to compare in-market data of the product to the target principle of the product, a score generator to determine an aggregate score of the product based on the comparison, and an output generator to reduce discretionary input of an analyst by generating an output, the output including the aggregate score of the product and a recommended adjustment to the at least one lever.
An example system disclosed herein includes an analyzer to determine a first priming characteristic of media at a first location based on first neuro-response data and determine a second priming characteristic of the media at the second location based on second neuro-response data. The example system includes a selector to select a third location in the media after the first location or a fourth location in the media after the second location as a candidate location for introduction of advertising material based on the first priming characteristic and the second priming characteristic. The selector is to select the third location when the first priming characteristic indicates increased receptivity to the advertising material at the first location relative to the second priming characteristic and select the fourth location when the second priming characteristic indicates increased receptivity to the advertising material at the second location relative to the first priming characteristic.
Methods, apparatus, systems, and articles of manufacture are disclosed herein to associate a data collector with a class by executing a classification model using a first data collector characteristic, the first data collector characteristic corresponding to the data collector, the classification model generated by applying a learning algorithm to classification training data, the classification training data including second data collector characteristics of a training group, select the class based on a requested characteristic of a task request from a distribution agent, select the data collector associated with the class, and send the selection to the distribution agent.
Methods, apparatus, and articles manufacture to decode documents based on images using artificial intelligence are disclosed. An example apparatus includes a model executor to input an image into a first artificial intelligence (AI)-based model to generate detected columns of text in the image; and input the image into a second AI-based model to classify the detected columns into categories; a cell identifier to identify rows or cells in the detected columns; and a report generator to: link information corresponding to the rows or cells in the detected columns with corresponding categories; and generating a report based on the linked information.
G06V 30/413 - Classification of content, e.g. text, photographs or tables
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 40/18 - Editing, e.g. inserting or deleting using ruled lines of spreadsheets
G06F 40/58 - Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
G06V 30/412 - Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables
G06V 30/414 - Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text
Example methods, apparatus, and articles of manufacture to classify labels based on images using artificial intelligence are disclosed. An example apparatus includes a regional proposal network to determine a first bounding box for a first region of interest in a first input image of a product; and determine a second bounding box for a second region of interest in a second input image of the product; a neural network to: generate a first classification for a first label in the first input image using the first bounding box; and generate a second classification for a second label in the second input image using the second bounding box; a comparator to determine that the first input image and the second input image correspond to a same product; and a report generator to link the first classification and the second classification to the product.
Methods and apparatus are disclosed to model consumer choices. An example method includes adding, with a processor, a set of products having respondent choice data to a base multinomial logit (MNL) model, the base MNL model including an item utility parameter and a price utility parameter associated with corresponding ones of products in the set of products, generating, with the processor, a number of copies of the base MNL model to form an aggregate model based on a number of the corresponding ones of products in the set of products, each one of the number of copies of the base MNL model exhibiting an effect of an independence of irrelevant alternatives (IIA) property, proportionally affecting interrelationships, with the processor, between dissimilar ones of the number of products in the set by inserting sourcing effect values in the aggregate model to be subtracted from respective ones of the item utility parameters, estimating, with the processor, the item utility parameters of the aggregate model based on the number of copies of the base MNL model and the respondent choice data, and calculating, with the processor, the choice probability for the corresponding ones of the products in the set of products based on the estimated item utility parameters and the price utility parameters.
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
An example apparatus includes a feature extractor to generate a first image descriptor based on a first image of a first retail product tag corresponding to a first category, the first image descriptor representative of one or more visual features of the first retail product tag; a feature descriptor generator to generate a feature descriptor corresponding to the first retail product tag by concatenating the first image descriptor and a first category signature corresponding to the first retailer category; and a classifier to generate a first probability value corresponding to a first type of promotional product tag and a second probability value corresponding to a second type of promotional product tag based on the feature descriptor; and determine whether the first retail product tag corresponds to the first type of promotional product tag or the second type of promotional product tag based on the first and second probability values.
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06T 7/77 - Determining position or orientation of objects or cameras using statistical methods
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
49.
Content based selection and meta tagging of advertisement breaks
An example system to identify an advertisement to include in source material to increase an effectiveness of the advertisement includes an analyzer to determine one or more priming characteristics for a plurality of locations of a source material based on neuro-response data collected from a first subject exposed to the source material and a selector to identify an attribute of the advertisement, identify at least one of a temporal attribute or a spatial attribute for the plurality of locations, perform a comparison of the attribute of the advertisement to the at least one of the temporal attribute or the spatial attribute for the plurality of locations, select a first location of the plurality of locations for insertion of the advertisement based on the comparison and the priming characteristics, and transform the source material to include the advertisement at the first location.
A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
50.
Methods, systems, articles of manufacture, and apparatus to monitor the availability of products for purchase
Methods, systems, articles of manufacture, and apparatus to monitor the availability of products for purchase are disclosed. An apparatus includes a communications interface to receive market data from data collectors, the market data including stock status data indicative of different stock statuses for a product in different retail establishments. The apparatus further includes a reward profile analyzer reduce error in collection of the stock status data by: generating a reward profile for the market data, the reward profile to define different reward levels for different types of the stock statuses indicated by the stock status data; determining a distribution of rewards among the different data collectors based on the reward profile and different portions of the market data provided by corresponding ones of the different data collectors; and providing the rewards to the different data collectors based on the distribution.
Systems and methods for measuring biologically and behaviorally based responses to social media, locations, or experiences and providing instant and continuous feedback in response thereto are disclosed. An example system includes a first sensor to determine an emotional response of a user exposed to a social media application, a second sensor to determine a current activity of the user, and a third sensor to determine an environment of the user. The example system also establishes a priority schedule based on the emotional response, the current activity, and the environment. The system also correlates, based on the priority schedule, an advertisement with at least one of the emotional response, activity, or the environment. In addition, the example system presents the advertisement based on the priority schedule and the correlation of the advertisement with the at least one of the activity, the environment, or the emotional response.
A61B 3/11 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring interpupillary distance or diameter of pupils
A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/16 - Devices for psychotechnics; Testing reaction times
Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus for processing a receipt associated with a user disclosed herein includes an optical character recognition engine to generate bounding boxes, respective ones of the bounding boxes associated with groups of characters detected in the receipt, the bounding boxes including a first bounding box, a second bounding box and a third bounding box, a word connector to connect the first bounding box to the second bounding box based on (1) an adjacency of the first bounding box to the second bounding box and (2) a difference value from a comparison of a location of the first bounding box to a location of the second bounding box, a line connector to form a line of the ones of the bounding boxes by connecting the third bounding box to the second bounding based on a relationship between the first bounding box and the second bounding box, the line of the ones of the bounding boxes indicative of related receipt fields, and a creditor to generate a report based on the line.
Methods, apparatus, systems and articles of manufacture are disclosed to identify affinity between segment attributes and product characteristics. An example method includes identifying, with a processor, a set of product characteristics from purchase transactions that exhibit a threshold product affinity, selecting, with the processor, a set of products having at least one product characteristic from the set of product characteristics that exhibit the threshold product affinity, the set of products associated with first segments, extracting, with the processor, segment attributes from the first segments, and improving a market success of the product of interest by identifying, with the processor, target segments based on ones of the extracted segment attributes exhibiting a threshold segment affinity.
An example system disclosed herein includes an analyzer to analyze first neuro-response data and second neuro-response data and a selector to identify a candidate location in source material for introduction of an advertisement or entertainment based on first neuro-response data and second neuro-response data. The analyzer is to detect a first pattern of oscillation in a first frequency band of third neuro-response data; detect a second pattern of oscillation in a second frequency band of the third neuro-response data; determine a degree of phase synchrony or amplitude synchrony based on the first pattern of oscillation and the second pattern of oscillation; and determine an effectiveness of the advertisement or entertainment based on the degree of phase synchrony or amplitude synchrony.
An ingredient data system that ingests text and graphics of product labels associated with consumer products to check compliance with rules pertaining to what can be included on the product labels generally includes a memory having instructions stored thereon, and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the base attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products designated under one or more of the base attributes associated with the first request, and at least a portion of details of noncompliance when one or more of the pieces of the constituent information are identified as impermissible according to the compliance information.
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G06K 7/10 - Methods or arrangements for sensing record carriers by corpuscular radiation
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
Methods and apparatus are disclosed for facilitating, via an interactive display platform, a sales transaction conducted in real time between a consultant associated with a consultant device and a customer associated with a customer device. Independent user interaction control capabilities are assigned to the consultant device and the customer device for controlling the sharing of information, the identification of selections pertaining to the shared information and the population of a virtual shopping cart based on the selections, and/or for interacting with the shared information, selections and populated virtual shopping cart. The disclosed methods and apparatus can facilitate a sales transaction involving any type of product and/or service, including the sale of a report containing product data.
Example devices are disclosed herein that include a first elongated band coupled to a first housing to be located on a first side of a head of a subject and a second housing to be located near a second side of the head of the subject, the first elongated band comprising a first set of electrodes. The example device also includes a second elongated band coupled to the first housing and to the second housing, the second elongated band comprising a second set of electrodes. In addition, the device includes a third elongated band coupled to the first housing and to the second housing, the third elongated band comprising a third set of electrodes.
A method comprises displaying visual representations of a plurality of product alternatives each including at least one attribute variant to a respondent, receiving from the respondent an indication of a preferred one of the plurality of product alternatives, transmitting a request to the respondent to identify at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives and receiving a response from the respondent identifying at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives.
Methods and apparatus to search datasets are disclosed. An example disclosed method includes receiving a search request having at least two criteria and assigning the criteria to a first group according to a logical relationship between the criteria. The example method further includes determining which of the criteria in the first group is satisfied by a least amount of records in a database based on a plurality of counts, the counts respectively indicative of a number of corresponding records in the database satisfying a respective one of criteria exhibited by the database, and identifying a reduced set of records in the database to be searched, the reduced set of records corresponding to the first or second criteria that is satisfied by the least amount of records in the database, and reducing a search time associated with the search request by searching the reduced set of records from the database.
Methods, apparatus, systems and articles of manufacture to adjust content presented to an individual are disclosed. An example system includes a first modality sensor to measure a first response of an individual to first content during a first time frame and a second modality sensor to measure a second response of the individual to the first content during the first time frame. The first modality sensor is to measure a third response of the individual to first content during a second time frame, and the second modality sensor is to measure a fourth response of the individual to the first content during the second time frame. The example system also includes a mental classifier executing instructions to determine a first mental classification of the individual based on a first comparison of the first response to a first threshold and a second comparison of the second response to a second threshold. The mental classifier also is to determine a second mental classification of the individual based on a third comparison of the third response to a third threshold and a fourth comparison of the fourth response to a fourth threshold. In addition, the mental classified is to determine a mental state of the individual based on a degree of similarity between the first mental classification and the second mental classification. The example system also includes a content modifier to at least one of modify the first content to include second content or replace the first content with second content based on the mental state.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
A61B 3/11 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring interpupillary distance or diameter of pupils
A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
A61B 5/16 - Devices for psychotechnics; Testing reaction times
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
H04N 21/4415 - Acquiring end-user identification using biometric characteristics of the user, e.g. by voice recognition or fingerprint scanning
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
H04N 21/458 - Scheduling content for creating a personalised stream, e.g. by combining a locally stored advertisement with an incoming stream; Updating operations, e.g. for OS modules
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
An example system includes an analyzer to identify first activity in first neuro-response data, the first activity generated in response to exposure of a subject to a first stimulus prior to exposure to an advertisement or entertainment; identify second activity in second neuro-response data, the second activity generated in response to re-exposure of the subject to the first stimulus after to exposure to the advertisement or entertainment; calculate a differential event related potential measurement; and calculate a differential event related power spectral perturbation. The example system includes a resonance estimator to determine a subject resonance measurement to the advertisement or the entertainment based on the differential event related potential measurement and adjust at least one of the subject resonance measurement or the differential event related potential measurement based on the differential event related power spectral perturbation to generate an adjusted subject resonance measurement.
An example system includes an analyzer to identify a degree of amplitude synchrony between a first pattern in a first frequency band in first neuro-response data and a second pattern in a second frequency band in the first neuro-response data, the first neuro-response data gathered via a first modality of collection from a subject while the subject is exposed to media, and modify the degree of amplitude synchrony in response to activity in second neuro-response data, the second neuro-response data gathered via a second modality of collection from the subject while the subject is exposed to the media, the activity corresponding in time to at least a portion of the first pattern or the second pattern. The example system includes an estimator to determine an effectiveness of the media based on the modified degree of amplitude synchrony.
An example system includes an analyzer to determine a first distance between (1) a first peak in a first frequency band of first neuro-response data gathered from a subject while exposed to media and (2) a second peak in the first frequency band; determine a second distance between (1) a third peak in the first frequency band and either (2) the second peak in the first frequency band or (3) a fourth peak in the first frequency band and determine a first difference between the first distance and the second distance. The example system includes a selector to determine a modification for the media based on the first difference and a modifier to implement the modification for presentation of the media.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
A61B 5/16 - Devices for psychotechnics; Testing reaction times
A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.
Example headsets and electrodes are described herein. Example electrode units described herein include a housing having a cavity defined by an opening in a side of the housing and an electrode. In some such examples, the electrode includes a ring disposed in the opening and an arm, where the arm has a first portion extending outward from the opening away from the housing and a second portion extending from an end of the first portion toward the housing and into the cavity, and the first and second portions connect at a bend.
A61B 5/05 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/291 - Bioelectric electrodes therefor specially adapted for particular uses for electroencephalography [EEG]
67.
Device and method for sensing electrical activity in tissue
An exemplary embodiment providing one or more improvements includes apparatus and methods for sensing electrical activity in tissue of a person in a manner which is substantially limits or eliminates interference from noise in a surrounding environment.
An example system includes a first headset including first sensor to gather first user data from a first subject during exposure to media, the first user data including at least one of psychophysiological data or physiological data; and a first processor to generate first data indicative of an emotional response of the first subject based on the first user data. The example system includes a second headset including a second sensor to gather second user data from the second subject during exposure to the media, the second user data including at least one of psychophysiological data or physiological data; a second processor to generate second data indicative of an emotional response of the second subject based on the second user data and synchronize the second data with the first data to generate synchronized response data; and a second transmitter to transmit the synchronized response data to a central processor.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/16 - Devices for psychotechnics; Testing reaction times
H04N 7/16 - Analogue secrecy systems; Analogue subscription systems
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/475 - End-user interface for inputting end-user data, e.g. PIN [Personal Identification Number] or preference data
A61B 5/377 - Electroencephalography [EEG] using evoked responses
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
H04H 60/33 - Arrangements for monitoring the users' behaviour or opinions
69.
Methods, systems, articles of manufacture and apparatus to monitor auditing devices
Methods, apparatus, systems and articles of manufacture are disclosed to monitor auditing devices. An example apparatus includes a workload analyzer to obtain alert data related to a potential new product from an auditing device, and a product analyzer to identify a product within the alert data to determine if the product has been previously identified by another auditing device. In response to determining that the product has not been previously identified, the example apparatus includes an alert analyzer to cluster the alert data based on characteristics associated with an auditor profile of the auditing device, and determine a probability of transmitting the alert data to other auditing devices based on the clustered alert data. The example apparatus also includes an alert authorizer to suppress the alert data from being transmitted to the other auditing devices to reduce an amount of network resources required for subsequent processing when the probability does not satisfy a threshold.
G06Q 50/00 - Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
70.
Methods and apparatus to perform image analyses in a computing environment
An example apparatus includes a feature extractor to generate a first image descriptor based on a first image of a first retail product tag corresponding to a first category, the first image descriptor representative of one or more visual features of the first retail product tag; a feature descriptor generator to generate a feature descriptor corresponding to the first retail product tag by concatenating the first image descriptor and a first category signature corresponding to the first retailer category; and a classifier to generate a first probability value corresponding to a first type of promotional product tag and a second probability value corresponding to a second type of promotional product tag based on the feature descriptor; and determine whether the first retail product tag corresponds to the first type of promotional product tag or the second type of promotional product tag based on the first and second probability values.
An apparatus includes a feature extractor to generate image descriptors based on retail product tag images corresponding to a retailer category; a probability density function generator to generate a probability density function of probability values corresponding to visual features represented in the image descriptors; a sample selector to select ones of the probability values based on a sample selection algorithm that identifies positions in the probability density function of the ones of the probability values to be selected; a category signature generator to generate a category signature based on the selected ones of the probability values; and a processor to train a convolutional neural network (CNN) based on a feature descriptor and one of the retail product tag images, the feature descriptor including the category signature concatenated to one of the image descriptors, the training to cause the CNN to classify the one of the retail product tag images as a type of product tag.
Methods, apparatus, systems and articles of manufacture methods, systems, apparatus and articles of manufacture to model ecommerce sales are disclosed. A system to model to eCommerce sales includes a trend identifier to compute commerce metric differences corresponding to products, the commerce metric differences based on first commerce metrics scraped at a first time and second commerce metrics scraped at a second time, a splitter to split the commerce metric differences into a first portion of the commerce metric differences corresponding to a first dataset of eCommerce cooperators, and into a second portion of the commerce metric differences corresponding to a second dataset of eCommerce non-cooperators, a machine learning engine to infer sales data by estimating eCommerce non-cooperators sales based on the second portion of the commerce metric differences, and a sales allocator to estimate sales missing from collected sales data based on the estimate eCommerce non-cooperators sales.
An ingredient data system that ingests text and graphics of product labels associated with consumer products to check compliance with rules pertaining to what can be included on the product labels generally includes a memory having instructions stored thereon, and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the base attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products designated under one or more of the base attributes associated with the first request, and at least a portion of details of noncompliance when one or more of the pieces of the constituent information are identified as impermissible according to the compliance information.
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G06K 7/10 - Methods or arrangements for sensing record carriers by corpuscular radiation
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.
Methods, systems and apparatus are disclosed to model consumer choices. An example apparatus includes a multinomial logit (MNL) engine to add a set of products having respondent choice data to a base MNL model, an aggregate building engine to improve a computational efficiency of model generation by generating a number of copies of the base MNL model, each one of the number of copies of the base MNL model exhibiting an effect of an independence or irrelevant alternatives (HA) property, a sourcing modifier to proportionally affect interrelationships between dissimilar ones of the number of products in the set by inserting sourcing effect values in the aggregate model, an estimator to estimate the item utility parameters of the aggregate model based on the number of copies of the base MNL model and the respondent choice data, and a simulation engine to calculate the choice probability.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06N 7/00 - Computing arrangements based on specific mathematical models
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
76.
Generating ratings predictions using neuro-response data
An example system disclosed herein for transforming neuro-response data into media ratings includes a data collector to obtain first neuro-response from a first subject exposed to a first media and second neuro-response data from a second subject exposed to a second media. The first media broadcast is before a time of the second media. The example system includes an analyzer to integrate the first neuro-response data with ratings data for the first media to generate a first rating for the first media. The ratings data is based on set-top box data associated with a media presentation device presenting the first media. The analyzer is to transform the second neuro-response data into a second rating for the second media based on the first rating.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
Examples methods, apparatus/systems and articles of manufacture for auditing point-of-sale images are disclosed herein. Example methods disclosed herein include comparing a region of interest of an image displayed via a user interface with a plurality of reference product images stored in a database to identify a plurality of candidate product images from the plurality of reference product images as potential matches to a first product depicted in the image. For example, the candidate product images are associated with respective confidence levels indicating respective likelihoods of matching the first product. Disclosed example methods also include displaying, via the user interface, the candidate product images simultaneously with the image in a manner based on the respective confidence levels, and automatically selecting a first one of the candidate product images as matching the first product based on the respective confidence levels.
G06F 16/51 - Indexing; Data structures therefor; Storage structures
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06T 11/60 - Editing figures and text; Combining figures or text
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
Methods, systems, apparatus, and tangible non-transitory carrier media encoded with one or more computer programs for classifying an item. In accordance with particular embodiments, a labeling task is issued to workers participating in a crowdsourcing system. The labeling task includes evaluating an inferred classification that includes one or more of the class labels in a hierarchical classification taxonomy based at least in part on a description of the item and the class labels in the classification. Evaluation decisions are received from the crowdsourcing system. The classification is validated based on the evaluation decisions to obtain a validation result. The validating includes applying at least one consensus criterion to an aggregation of the received evaluation decisions. Data corresponding to one or more of the class labels in the classification is routed to respective destinations based on the validation result.
An example system disclosed herein includes an analyzer to determine a first priming characteristic of media at a first location based on first neuro-response data and determine a second priming characteristic of the media at the second location based on second neuro-response data. The example system includes a selector to select a third location in the media after the first location or a fourth location in the media after the second location as a candidate location for introduction of advertising material based on the first priming characteristic and the second priming characteristic. The selector is to select the third location when the first priming characteristic indicates increased receptivity to the advertising material at the first location relative to the second priming characteristic and select the fourth location when the second priming characteristic indicates increased receptivity to the advertising material at the second location relative to the first priming characteristic.
A61B 5/16 - Devices for psychotechnics; Testing reaction times
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
G09B 7/073 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers providing for individual presentation of questions to a plurality of student stations all student stations being capable of presenting the same questions simultaneously
G09B 5/10 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations all student stations being capable of presenting the same information simultaneously
A61B 3/11 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring interpupillary distance or diameter of pupils
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G09B 5/06 - Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
The present invention is directed to a method and system for predicting the behavior of an audience based on the biologically based responses of the audience to a presentation that provides a sensory stimulating experience and determining a measure of the level and pattern of engagement of that audience to the presentation. In particular, the invention is directed to a method and system for predicting whether an audience is likely to view a presentation in its entirety. In addition, the present invention may be used to determine the point at which an audience is likely to change their attention to an alternative sensory stimulating experience including fast forwarding through recorded content, changing the channel or leaving the room when viewing live content, or otherwise redirecting their engagement from the sensory stimulating experience.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
A system evaluates source materials such as videos, imagery, web pages, text, etc., in order to determine priming characteristics associated with the source materials. The system also obtains user preferences such as user interests, purchase history, location information, etc. The priming characteristics and user characteristics are blended to obtain blended attributes. The blended attributes are correlated with stimulus material attributes to intelligently and dynamically select stimulus material such as marketing, entertainment, informational materials, etc., for introduction into the source material. The stimulus material may be inserted in real-time or near real-time into the source material for delivery to a user.
Methods and apparatus are disclosed for facilitating, via an interactive display platform, a sales transaction conducted in real time between a consultant associated with a consultant device and a customer associated with a customer device. Independent user interaction control capabilities are assigned to the consultant device and the customer device for controlling the sharing of information, the identification of selections pertaining to the shared information and the population of a virtual shopping cart based on the selections, and/or for interacting with the shared information, selections and populated virtual shopping cart. The disclosed methods, systems, and apparatus can facilitate a sales transaction involving any type of product and/or service, including the sale of a report containing product data.
G06Q 30/06 - Buying, selling or leasing transactions
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
85.
Neuro-response stimulus and stimulus attribute resonance estimator
Example methods, systems, and machine readable media are disclosed herein for determining a subject resonance measurement. An example method includes accessing first neuro-response data obtained from a subject prior to exposure to an advertisement or entertainment and second neuro-response data obtained from the subject after exposure to the advertisement or the entertainment, respectively. The example method includes calculating, using a processor, a first event related potential measurement and a second event related potential measurement based on the first neuro-response data and the second neuro-response data. The example method includes calculating, using the processor, a differential event related potential measurement based on the first event related potential measurement and the second event related potential measurement. In addition, the example method includes determining a subject resonance measurement to the advertisement or the entertainment based on the differential event related potential measurement.
Methods, apparatus, systems and articles of manufacture are disclosed to identify affinity between segment attributes and product characteristics. An example method includes identifying, with a processor, a set of product characteristics from purchase transactions that exhibit a threshold product affinity, selecting, with the processor, a set of products having at least one product characteristic from the set of product characteristics that exhibit the threshold product affinity, the set of products associated with first segments, extracting, with the processor, segment attributes from the first segments, and improving a market success of the product of interest by identifying, with the processor, target segments based on ones of the extracted segment attributes exhibiting a threshold segment affinity.
An example system disclosed herein includes an analyzer to analyze first neuro-response data from a first frequency band of a first subject exposed to source material and second neuro-response data from a second frequency band of the first subject and a selector to identify a candidate location in the source material for introduction of an advertisement or entertainment based on a degree of coherence between a first change in amplitude of the first frequency band measured before a neurological event and a second change in amplitude of the second frequency band measured before the neurological event. The analyzer is to analyze third neuro-response data from at least one of the first subject or a second subject exposed to a combination of the source material and the advertisement or entertainment inserted in the candidate location and determine an effectiveness of the advertisement or entertainment based on the third neuro-response data.
An example system to identify an advertisement to include in source material to increase an effectiveness of the advertisement includes an analyzer to determine one or more priming characteristics for a plurality of locations of a source material based on neuro-response data collected from a first subject exposed to the source material and a selector to identify an attribute of the advertisement, identify at least one of a temporal attribute or a spatial attribute for the plurality of locations, perform a comparison of the attribute of the advertisement to the at least one of the temporal attribute or the spatial attribute for the plurality of locations, select a first location of the plurality of locations for insertion of the advertisement based on the comparison and the priming characteristics, and transform the source material to include the advertisement at the first location.
A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
89.
Neuro-physiology and neuro-behavioral based stimulus targeting system
An example system includes a processor to determine a first distance between a first peak in a first frequency band of neuro-response data gathered from a subject while exposed to media and a second peak in the first frequency band; determine a second distance between a third peak in the first frequency band and either the second peak in the first frequency band or a fourth peak in the first frequency band; determine a first difference between the first distance and the second distance; generate a first response profile for the subject based on the first difference; and integrate the first response profile with a second response profile associated with a second subject to form an integrated response profile. A selector is to select an advertisement or entertainment for presentation based on the integrated response profile. The processor is to modify the media to present the advertisement or entertainment.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
A61B 5/16 - Devices for psychotechnics; Testing reaction times
An example system disclosed herein includes an analyzer to determine a first priming characteristic of media at a first location based on first neuro-response data and determine a second priming characteristic of the media at the second location based on second neuro-response data. The example system includes a selector to select a third location in the media after the first location or a fourth location in the media after the second location as a candidate location for introduction of advertising material based on the first priming characteristic and the second priming characteristic. The selector is to select the third location when the first priming characteristic indicates increased receptivity to the advertising material at the first location relative to the second priming characteristic and select the fourth location when the second priming characteristic indicates increased receptivity to the advertising material at the second location relative to the first priming characteristic.
Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.
An ingredient data system that ingests text and graphics of product labels associated with consumer products generally includes a memory having instructions stored thereon; and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the master attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products having one or more of the master attributes associated with the first request, and at least a portion of each of the images of one or more of the product labels associated with the related consumer products having the at least one master attribute different from one or more of the master attributes associated with the first request.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
93.
Information management system for product ingredients that produces hybrid data offerings combining product information data and analytic data
An ingredient data system that ingests text and graphics of product labels associated with consumer products generally includes a memory having instructions stored thereon; and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the master attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products having the one or more master attributes associated with the first request and at least a portion of the sales history, and at least a portion of each of the images of one or more of the product labels associated with the related consumer products and at least a portion of a sales history.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
94.
Information management system for product ingredients to allow regulatory compliance checks
An ingredient data system that ingests text and graphics of product labels associated with consumer products to check compliance with rules pertaining to what can be included on the product labels generally includes a memory having instructions stored thereon, and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the base attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products designated under one or more of the base attributes associated with the first request, and at least a portion of details of noncompliance when one or more of the pieces of the constituent information are identified as impermissible according to the compliance information.
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
G06K 7/10 - Methods or arrangements for sensing record carriers by corpuscular radiation
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
G06K 9/32 - Aligning or centering of the image pick-up or image-field
95.
Methods and apparatus to forecast new product launch sourcing
Methods and apparatus are disclosed to forecast new product launch sourcing. An example method includes identifying shared attributes between the new product and a plurality of existing products in the target market, calculating theoretical co-penetration values between the attributes shared between the new product and at least one of the plurality of existing products, calculating actual co-penetration values between the attributes shared between the new product and at least one of the plurality of existing products, calculating an attribute distance value between corresponding ones of the theoretical and actual co-penetration values, and calculating a percent volume of the new product expected to be sourced from one of the plurality of existing products based on the attribute distance value.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
96.
Analysis of marketing and entertainment effectiveness using central nervous system, autonomic nervous system, and effector data
Example apparatus, systems, machine readable media, and methods are disclosed herein for transforming neuro-response data collected using a first modality and a second modality into a measure of effectiveness of an advertisement or entertainment. An example system includes an analyzer to analyze first neuro-response data gathered from a subject while exposed to an advertisement or entertainment using the first modality, the first neuro-response data including electroencephalographic data including a first frequency band and a second frequency band. The example system also includes a processor to identify a degree of phase synchrony between a first pattern of oscillation in the first frequency band and a second pattern of oscillation in the second frequency band. The processor also is to synthesize the first neuro-response data with second neuro-response data gathered from the subject while exposed to the advertisement or entertainment using the second modality by: recognizing a signature in the electroencephalographic data corresponding to an activity of the second neuro-response data; and adjusting the degree of phase synchrony based on the signature. The example system also includes an estimator to determine an effectiveness of the advertisement or entertainment based on the adjusted degree of phase synchrony.
Methods, apparatus, systems and articles of manufacture to adjust content presented to an individual are disclosed. An example system includes a first modality sensor to measure a first response of an individual to first content during a first time frame and a second modality sensor to measure a second response of the individual to the first content during the first time frame. The first modality sensor is to measure a third response of the individual to first content during a second time frame, and the second modality sensor is to measure a fourth response of the individual to the first content during the second time frame. The example system also includes a mental classifier executing instructions to determine a first mental classification of the individual based on a first comparison of the first response to a first threshold and a second comparison of the second response to a second threshold. The mental classifier also is to determine a second mental classification of the individual based on a third comparison of the third response to a third threshold and a fourth comparison of the fourth response to a fourth threshold. In addition, the mental classified is to determine a mental state of the individual based on a degree of similarity between the first mental classification and the second mental classification. The example system also includes a content modifier to at least one of modify the first content to include second content or replace the first content with second content based on the mental state.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
A61B 5/053 - Measuring electrical impedance or conductance of a portion of the body
A61B 3/11 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for measuring interpupillary distance or diameter of pupils
A61B 3/113 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for determining or recording eye movement
A61B 5/16 - Devices for psychotechnics; Testing reaction times
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
H04N 21/4415 - Acquiring end-user identification using biometric characteristics of the user, e.g. by voice recognition or fingerprint scanning
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
H04N 21/458 - Scheduling content for creating a personalised stream, e.g. by combining a locally stored advertisement with an incoming stream; Updating operations, e.g. for OS modules
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
A system generates a first layer of information that includes in combination information from the product label and attributes determined from the information from the product label but not listed on the product label. The system also generates a second layer of information that populates the second layer of information with information from the first layer of information, receives changes to the second layer of information from one of the retailer and the brand owner associated with the populated information from the first layer of information, and publishes the second layer of information with the changes from one of the retailer and the brand owner to the portion of the electronic label. The system accepts changes from one of the retailer and the brand owner to the second layer of information and prevents changes to the first layer of information from one of the retailer and the brand owner.
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G06Q 30/06 - Buying, selling or leasing transactions
G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
G06K 9/46 - Extraction of features or characteristics of the image
G06K 7/10 - Methods or arrangements for sensing record carriers by corpuscular radiation
G06K 19/06 - Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
99.
Methods and apparatus to identify retail pricing strategies
Methods and apparatus to identify retail pricing strategies are disclosed herein. An example apparatus for identifying a pricing strategy employed by a store includes a calculator to calculate a first pricing strategy variable for the store based on sales data of the store. The example apparatus includes an index creator to index the first pricing strategy variable against aggregated data for a plurality of stores to generate a pricing index. The example apparatus includes a pricing strategy identifier to identify a pricing strategy for the store based on the pricing index.
Example devices are disclosed herein that include a first elongated band coupled to a first housing to be located on a first side of a head of a subject and a second housing to be located near a second side of the head of the subject, the first elongated band comprising a first set of electrodes. The example device also includes a second elongated band coupled to the first housing and to the second housing, the second elongated band comprising a second set of electrodes. In addition, the device includes a third elongated band coupled to the first housing and to the second housing, the third elongated band comprising a third set of electrodes.
patents
