A system for training a learning machine accesses a training database of reference metadata that describes reference plans that include reference first-type plans and reference second-type plans. Such plans may be travel plans or other plans. The system trains the learning machine to distinguish candidate first-type plans from candidate second-type plans. The training of the learning machine is based on a set of decision trees generated from randomly selected subsets of the reference metadata, and the randomly selected subsets each describe a corresponding randomly selected portion of the reference plans. The system then modifies the trained learning machine based on asymmetrical penalties for incorrectly distinguishing candidate first-type plans from candidate second-type plans. The system then provides the modified learning machine for run-time use in classifying plans.
A system for training a learning machine accesses a training database of reference metadata that describes reference plans that include reference first-type plans and reference second-type plans. Such plans may be travel plans or other plans. The system trains the learning machine to distinguish candidate first-type plans from candidate second-type plans. The training of the learning machine is based on a set of decision trees generated from randomly selected subsets of the reference metadata, and the randomly selected subsets each describe a corresponding randomly selected portion of the reference plans. The system then modifies the trained learning machine based on asymmetrical penalties for incorrectly distinguishing candidate first-type plans from candidate second-type plans. The system then provides the modified learning machine for run-time use in classifying plans.
Example embodiments provide a system and method for inferring preferences from message metadata and conversations. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including inferring a preference of a user among the one or more users based on metadata in the communication. The networked system triggers a search process based in part on the inferred preference. The networked system then generates and transmits to the user a customized response comprising results of the search process.
A travel search machine generates a trip object defined by a corresponding trip identifier. The trip object may have a corresponding trip data structure to which one or more search results may be assigned by a user. For example, the travel search machine may be configured to receive a trip identifier as a submission from a user device, generate a trip data structure corresponding to the trip identifier, and responsive to a received command from a user device, assign one or more search results to the trip data structure, such that reference to the trip data structure via the received trip identifier causes a presentation of at least some of the one or more search results assigned to the trip data structure.
Example embodiments described herein disclose a travel search machine configured to retrieve and present search results as graphical elements within a graphical user interface. The travel search machine presents graphical elements with a slider configured to define a subset of the search results, where the subset is defined by a location of the slider among the graphical elements within the graphical user interface, and is further configured to receive a user input that moves the slider from a first location in the graphical user interface to a second location in the graphical user interface and in response to the first user input, cause the user device to display a notification window in the graphical user interface at a position relative to the slider in the first location, the notification window indicating a count of search results within the subset of search results defined by the location of the slider.
A server machine is configured to map an identifier of a user to an account of the user within a database. The server machine also embeds the identifier within a uniform resource locator (URL) that, when operated by a browser of the user, causes the browser to interact with a supplier server machine. The server machine later receives interaction result data from the supplier server machine, and the interaction result data includes the identifier of the user and an interaction detail resultant from the interaction initiated by the browser with the supplier server machine. A machine then detects that the interaction detail corresponds to the account of the user based on the identifier being both received in the interaction result data and mapped to the account of the user. Accordingly, the server machine causes inclusion of the interaction detail within an information entry that corresponds to the user.
Example embodiments provide a system and method for analyzing conversations and determining whether to participate with a response. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including parsing key terms from the communication. The networked system then identifies a sentiment of a user among the one or more users based on the parsed key terms. Based on the identified sentiment, the networked system determines whether to respond to the communication. In response to a determination to respond, the networked system generates a customized response and transmits the customized response, over the network, to a device of the user. The customized response may comprise questions or a set of options related to the conversation.
An item sharing machine is configured to receive share requests in the example form of allocation requests submitted by requesters for an allocable region of a graphical user interface. The allocation requests specify numerical values accorded to the allocable region by the requesters. The item sharing machine determines a distribution of the numerical values and, based on the distribution, generates an allocation plan defined by configuration parameters for the allocable region. The item sharing machine is configured to repeatedly update the allocable region based on the allocation plan by cyclically and selectively linking the allocable region to different computers of different requesters based on the allocation plan. The allocable region accordingly becomes linked to computers of different requesters at different times, and the item sharing machine is configured to cause one or more user devices to present the allocable region linked to such computers at different times.
G06F 9/451 - Execution arrangements for user interfaces
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
9.
Graphical user interface machine to present a window
Within a graphical user interface, a window may be spawned at one point in time and then populated with content at a later point in time. By execution of browser-executable code by a user's device and corresponding server-side code by a machine, a pop-under window may be spawned by the user's device. The spawned pop-under window may be initially hidden by the user's browser window and may be initially loaded with no content or default content. The device may monitor the graphical user interface for search criteria submitted by the user and update the spawned pop-under window based on such search criteria. If the user exits the webpage, and if rules allow presentation of a pop-under window, the pop-under window may be updated by the device for presentation to the user. Based on interest or lack of interest in the updated content, the user may revisit the website.
A machine is configured to access a search phrase or other communicated phrase and deconstruct the accessed phrase into multiple sub-phrases. The machine performs an analysis of n-grams that occur within the sub-phrases, generates a set of potentially different sub-phrases from the n-grams, and selects which data source among multiple available video sources should be accessed for each generated sub-phrase in the generated set. For example, the machine may allocate each generated sub-phrase to a corresponding data source and cause the corresponding data source to execute a query based on its corresponding sub-phrase. Thus, the machine chooses from which data source to obtain partial search results that correspond to each sub-phrase generated based on the analyzed n-grams in the accessed phrase.
A machine is configured to perform an example method that causes the machine to parse sub-phrases within a phrase, recognize that a sub-phrase has or can have a geographically specific meaning, and notify a user that the sub-phrase is being processed using the geographically specific meaning. For example, supposing a user has communicated a phrase, the machine builds sub-phrases from the n-grams of the phrase and detects that an n-gram has a geographically specific meaning, thus disambiguating the n-gram. This disambiguation is performed using one or more geographically specific databases of n-grams. The machine determines that a geographical location is relevant to the n-gram, selects a specialized search procedure for the n-gram, and obtains search results using the selected specialized search procedure. The machine may also notify the user that the n-gram or a sub-phrase in which the n-gram appears is being processed using the geographically specific meaning.
A machine is configured by appropriate software, such as software modules, to function as recommendation machine configured to receive an incoming value from a submitter for an allocable region of a graphical user interface. The allocable region is associated by a first data-structure to a data-string. The recommendation is configured to identify an available correlation of the data-string within a second data-structure, and the recommendation machine is further configured to recommend an outgoing value to be offered by an operator of the machine for the available correlation.
A map lens may take the form of a shape that may be superimposed on a map displayed in the user interface, moved around the map by the user, and activated by the user to select a region of the map bounded by the map lens. Activation of the map lens may cause the user interface to display only those markers that are within the region bounded by the map lens. In situations where the user moves the map lens over unselected regions of the map, the user interface may dynamically show or hide markers on the map. This may have the effect of presenting to the user a visually uncluttered map in which markers are only shown in the region in which the user has expressed some interest, as indicated by the user moving the map lens to that region of the map.
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
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
G01C 21/36 - Input/output arrangements for on-board computers
G01C 21/26 - Navigation; Navigational instruments not provided for in groups specially adapted for navigation in a road network
14.
Display of calendar-based single user, single event travel options
Example embodiments provide a system and method for providing user interfaces comprising calendar-based suggestions of single user, single event travel options. The system accesses calendar data of the user, which indicates an event that the user is scheduled to attend, and extracts data for the event from the calendar data. The system constructs an application program interface (API) request by incorporating the extracted data for the event as one or more search criteria in the API request. The system transmits the API request to a provider server of at least one service provider. In response, the system receives results from the provider server(s), which comprise options determined to be compatible with the event based on the one or more search criteria in the API request. The system causes presentation of at least some of the options from the results determined to be compatible with the event.
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
An item sharing machine is configured to receive share requests submitted by requesters and specifying numerical values accorded to the shareable item by the requesters. The item sharing machine determines a distribution of the numerical values and generates an allocation plan based on the distribution of the numerical values, which include a first numerical value accorded by a first requester. The item sharing machine determines an allocated percentage at which the shareable item is allocated to the first requester and selects an alternative percentage at which the shareable item is allocable to the first requester. The item sharing machine calculates an alternative numerical value accordable to the shareable item and causes presentation of a notification that the shareable item is allocable to the first requester at the alternative percentage, conditioned upon a future share request indicating that the alternative numerical value is accorded to the shareable item.
An item sharing machine is configured to receive share requests in the example form of allocation requests submitted by requesters for an allocable region of a graphical user interface. The allocation requests specify numerical values accorded to the allocable region by the requesters. The item sharing machine determines a distribution of the numerical values and, based on the distribution, generates an allocation plan defined by configuration parameters for the allocable region. The item sharing machine is configured to repeatedly update the allocable region based on the allocation plan by cyclically and selectively linking the allocable region to different computers of different requesters based on the allocation plan. The allocable region accordingly becomes linked to computers of different requesters at different times, and the item sharing machine is configured to cause one or more user devices to present the allocable region linked to such computers at different times.
Example embodiments provide a system and method for analyzing conversations and determining whether to participate with a response. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including parsing key terms from the communication. The networked system then identifies a sentiment of a user among the one or more users based on the parsed key terms. Based on the identified sentiment, the networked system determines whether to respond to the communication. In response to a determination to respond, the networked system generates a customized response and transmits the customized response, over the network, to a device of the user. The customized response may comprise questions or a set of options related to the conversation.
Example embodiments provide a system and method for inferring preferences from message metadata and conversations. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including inferring a preference of a user among the one or more users based on metadata in the communication. The networked system triggers a search process based in part on the inferred preference. The networked system then generates and transmits to the user a customized response comprising results of the search process.
Example embodiments described herein disclose a travel search machine configured to retrieve and present search results as graphical elements within a graphical user interface. The travel search machine presents graphical elements with a slider configured to define a subset of the search results, where the subset is defined by a location of the slider among the graphical elements within the graphical user interface, and is further configured to receive a user input that moves the slider from a first location in the graphical user interface to a second location in the graphical user interface and in response to the first user input, cause the user device to display a notification window in the graphical user interface at a position relative to the slider in the first location, the notification window indicating a count of search results within the subset of search results defined by the location of the slider.
A travel search machine generates a trip object defined by a corresponding trip identifier. The trip object may have a corresponding trip data structure to which one or more search results may be assigned by a user. For example, the travel search machine may be configured to receive a trip identifier as a submission from a user device, generate a trip data structure corresponding to the trip identifier, and responsive to a received command from a user device, assign one or more search results to the trip data structure, such that reference to the trip data structure via the received trip identifier causes a presentation of at least some of the one or more search results assigned to the trip data structure.
A machine may generate and provide a message that updates itself when opened. Such a message may include a link that, when operated during display of the message by a user's device, causes the machine to generate an image that depicts updated information in the form of one or more updated parameters. For example, the machine may operate within a travel search engine and may generate and provide a message that includes a previously found search result and also includes a link to an image that, once generated, depicts an updated parameter for the search result. As part of displaying the message, the user's device may operate the link, which causes the machine to generate the image and provide the image to the device. The device receives the image and displays the message, which includes the search result and now also includes the image of the updated parameter.
Within a graphical user interface, a window may be spawned at one point in time and then populated with content at a later point in time. By execution of browser-executable code by a user's device and corresponding server-side code by a machine, a pop-under window may be spawned by the user's device. The spawned pop-under window may be initially hidden by the user's browser window and may be initially loaded with no content or default content. The device may monitor the graphical user interface for search criteria submitted by the user and update the spawned pop-under window based on such search criteria. If the user exits the webpage, and if rules allow presentation of a pop-under window, the pop-under window may be updated by the device for presentation to the user. Based on interest or lack of interest in the updated content, the user may revisit the website.
A map lens may take the form of a shape that may be superimposed on a map displayed in the user interface, moved around the map by the user, and activated by the user to select a region of the map bounded by the map lens. Activation of the map lens may cause the user interface to display only those markers that are within the region bounded by the map lens. In situations where the user moves the map lens over unselected regions of the map, the user interface may dynamically show or hide markers on the map. This may have the effect of presenting to the user a visually uncluttered map in which markers are only shown in the region in which the user has expressed some interest, as indicated by the user moving the map lens to that region of the map.
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
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
G01C 21/36 - Input/output arrangements for on-board computers
Calendar-based suggestion of travel options involves suggesting a travel option based on events stored in a calendar of a user. For example, a user in San Francisco may be scheduled for a business trip to New York, and the user's calendar may show a dinner reservation in San Francisco on Saturday, September 3 and business meeting in New York on Monday, September 5. A suggestion machine accesses calendar data of the user and travel data for several available travel options (e.g., flights from San Francisco to New York). Based on the accessed calendar data and travel data, the suggestion machine determines that one or more travel options (e.g., a flight on Sunday, September 4) are compatible with the dinner reservation and the business meeting on the user's calendar. The suggestion machine presents these compatible travel options to the user.
Calendar-based suggestion of travel options involves suggesting a travel option based on events stored in a calendar of a user. For example, a user in San Francisco may be scheduled for a business trip to New York, and the user's calendar may show a dinner reservation in San Francisco on Saturday, September 3 and business meeting in New York on Monday, September 5. A suggestion machine accesses calendar data of the user and travel data for several available travel options (e.g., flights from San Francisco to New York). Based on the accessed calendar data and travel data, the suggestion machine determines that one or more travel options (e.g., a flight on Sunday, September 4) are compatible with the dinner reservation and the business meeting on the user's calendar. The suggestion machine presents these compatible travel options to the user.
patents
