Abstract: Systems and methods are disclosed herein for training a model to accurately determine whether two phrases are conversationally connected. A media guidance application may detect a first phrase and a second phrase, translate each phrase to a string of word types, append each string to the back of a prior string to create a combined string, determine a degree to which any of the individual strings, matches any singleton template, and determine a degree to which the combined string matches any conversational template. Based on the degrees to which the individual and combination strings match the singleton and conversational templates, respectively, strengths of association are correspondingly updated.

Abstract: Systems and methods are disclosed herein for training a control system based on prior audio inputs. The disclosed systems and methods receive a non-lexical or interjectional audio input. State change indications are also received and stored by the system within a predefined period of time starting from the time the system received the audio input. The system then receives a subsequent audio input. If the audio inputs of both the audio input and the subsequent audio input match, and contextual information for the audio input and the subsequent audio input match, the system stores a match association, comprising a confidence factor, for the subsequent audio input to the audio input in the associative data structure. If the confidence factor is greater than a preconfigured confidence level, the system executes one or more functions based on stored state change indications.

Abstract: Systems and methods provided herein for a determining a meaning of an ambiguous term in a text segment based on a context term, a static knowledge graph and a temporal knowledge graph. These systems and methods access a first knowledge graph associated with the context term to determine a potential term that is the meaning of the unknown term. Upon determining that there are multiple potential terms in the first knowledge graph that could be the meaning of the unknown term, the systems and methods take into account the temporal dimension of relationships between entities for disambiguating the meaning of the unknown term. The systems and methods achieve this by determining a time stamp of the text segment and accessing a second knowledge graph associated with the first context term and related to the time stamp to determine the potential term that is the meaning of the first unknown term.

Abstract: Systems and methods provided herein for a determining a meaning of an ambiguous term in a text segment based on a context term, a static knowledge graph and a temporal knowledge graph. These systems and methods access a first knowledge graph associated with the context term to determine a potential term that is the meaning of the unknown term. Upon determining that there are multiple potential terms in the first knowledge graph that could be the meaning of the unknown term, the systems and methods take into account the temporal dimension of relationships between entities for disambiguating the meaning of the unknown term. The systems and methods achieve this by determining a time stamp of the text segment and accessing a second knowledge graph associated with the first context term and related to the time stamp to determine the potential term that is the meaning of the first unknown term.

Abstract: Systems and methods are described to address shortcomings in a conventional conversation system via a novel technique utilizing artificial neural networks to train the conversation system whether or not to continue context. In some aspects, an interactive media guidance application determines a type of conversation continuity in a natural language conversation comprising first and second queries. The interactive media guidance application determines a first token in the first query and a second token in the second query. The interactive media guidance application identifies entity data for the first and second tokens. The interactive media guidance application retrieves, from a knowledge graph, graph connections between the entity data for the first and second tokens. The interactive media guidance application applies this data as inputs to an artificial neural network.

Abstract: Systems and methods provide a media guidance application that recognizes a plurality of natural language search queries for identifying a set of search results. For example, a user may want to determine when the Yankees are playing their next baseball game. The user may structure their query in multiple ways, such as, “When are the Yankees playing?” “What time is the Yankees game?” “When is the next Yankees baseball game?” The user would expect the same result, a description of when the Yankees are playing, regardless of how the query is structured. The systems and methods enable a user to use a plurality of search queries when searching for items or information to get desired results.

Abstract: Methods and systems for identifying a meaning of an ambiguous term in a natural language query. The media guidance application isolates first and second terms from a query received from a user and identifies, in a knowledge graph, first and second pluralities of candidate components associated with the first and second terms. The first and second terms each having multiple candidate components indicates the first and second terms have ambiguous meanings. The media guidance application matches each candidate component of the first and second pluralities of candidate components to form a plurality of pairs and determines strength of association for each pair in the plurality of pairs. The media guidance application filters the plurality of pairs by strength of association for each pair and determines a plurality of possible meanings based on the filtered plurality of pairs. The media guidance application selects a meaning from the plurality of possible meanings.

Abstract: Systems and methods provide a media guidance application that recognizes a plurality of natural language search queries for identifying a set of search results. For example, a user may want to determine when the Yankees are playing their next baseball game. The user may structure their query in multiple ways, such as, “When are the Yankees playing?” “What time is the Yankees game?” “When is the next Yankees baseball game?” The user would expect the same result, a description of when the Yankees are playing, regardless of how the query is structured. The systems and methods enable a user to use a plurality of search queries when searching for items or information to get desired results.

Abstract: Systems and methods are disclosed herein for training a model to accurately determine whether two phrases are conversationally connected. A media guidance application may detect a first phrase and a second phrase, translate each phrase to a string of word types, append each string to the back of a prior string to create a combined string, determine a degree to which any of the individual strings, matches any singleton template, and determine a degree to which the combined string matches any conversational template. Based on the degrees to which the individual and combination strings match the singleton and conversational templates, respectively, strengths of association are correspondingly updated.

Abstract: Systems and methods are disclosed herein for identifying a category of a search term and providing search results subject to the identified category. These systems and methods may be performed by a media guidance application. The media guidance application may receive a search term that may correspond to different categories of items, and the media guidance application may identify a category that the search term is most likely related to using a hierarchical structure. The media guidance application may limit the search to the identified category of items.

Abstract: Systems and methods are provided for playing a summary of a scene related to a current scene from a media asset being played in a display. This may be accomplished by a media guidance application receiving a command to play a summary of a scene related to the current playback. The media guidance application then determines a scene or scenes related to the current scene and compiles a summary of the related scenes. The media guidance application may also compile summarized content of the current scene to catch a viewer watching summary up to the current scene when the summary is complete. The media guidance application generates for display, on a second display, the summary content.

Abstract: Methods and systems for identifying a meaning of an ambiguous term in a natural language query. The media guidance application isolates first and second terms from a query received from a user and identifies, in a knowledge graph, first and second pluralities of candidate components associated with the first and second terms. The first and second terms each having multiple candidate components indicates the first and second terms have ambiguous meanings. The media guidance application matches each candidate component of the first and second pluralities of candidate components to form a plurality of pairs and determines strength of association for each pair in the plurality of pairs. The media guidance application filters the plurality of pairs by strength of association for each pair and determines a plurality of possible meanings based on the filtered plurality of pairs. The media guidance application selects a meaning from the plurality of possible meanings.

Abstract: Systems and methods are disclosed herein for training a model to accurately determine whether two phrases are conversationally connected. A media guidance application may detect a first phrase and a second phrase, translate each phrase to a string of word types, append each string to the back of a prior string to create a combined string, determine a degree to which any of the individual strings matches any singleton template, and determine a degree to which the combined string matches any conversational template. Based on the degrees to which the individual and combination strings match the singleton and conversational templates, respectively, strengths of association are correspondingly updated.

Abstract: Systems and methods provide a media guidance application that recognizes a plurality of natural language search queries for identifying a set of search results. For example, a user may want to determine when the Yankees are playing their next baseball game. The user may structure their query in multiple ways, such as, “When are the Yankees playing?” “What time is the Yankees game?” “When is the next Yankees baseball game?” The user would expect the same result, a description of when the Yankees are playing, regardless of how the query is structured. The systems and methods enable a user to use a plurality of search queries when searching for items or information to get desired results.

Abstract: Systems and methods provide a media guidance application that recognizes a plurality of natural language search queries for identifying a set of search results. For example, a user may want to determine when the Yankees are playing their next baseball game. The user may structure their query in multiple ways, such as, “When are the Yankees playing?” “What time is the Yankees game?” “When is the next Yankees baseball game?” The user would expect the same result, a description of when the Yankees are playing, regardless of how the query is structured. The systems and methods enable a user to use a plurality of search queries when searching for items or information to get desired results.

Abstract: Systems and methods are provided herein for using a trained knowledge graph to accurately determine whether two phrases are conversationally connected. To this end, three phrases are received. The phrases are translated to strings of word types by determining what type of word each word of each phrase represents, and replacing each word of the first phrase with its respective type. A knowledge graph is then accessed to determine strengths of association between a combinations of each string of word types and any conversational category of a plurality of conversational categories. If any of the strengths of association exceed a threshold, the corresponding strings may be determined to be part of a conversation.

Abstract: Systems and methods provided herein for a determining a meaning of an ambiguous term in a text segment based on a context term, a static knowledge graph and a temporal knowledge graph. These systems and methods access a first knowledge graph associated with the context term to determine a potential term that is the meaning of the unknown term. Upon determining that there are multiple potential terms in the first knowledge graph that could be the meaning of the unknown term, the systems and methods take into account the temporal dimension of relationships between entities for disambiguating the meaning of the unknown term. The systems and methods achieve this by determining a time stamp of the text segment and accessing a second knowledge graph associated with the first context term and related to the time stamp to determine the potential term that is the meaning of the first unknown term.

Abstract: Systems and methods are described to address shortcomings in a conventional conversation system via a novel technique utilizing artificial neural networks to train the conversation system whether or not to continue context. In some aspects, an interactive media guidance application determines a type of conversation continuity in a natural language conversation comprising first and second queries. The interactive media guidance application determines a first token in the first query and a second token in the second query. The interactive media guidance application identifies entity data for the first and second tokens. The interactive media guidance application retrieves, from a knowledge graph, graph connections between the entity data for the first and second tokens. The interactive media guidance application applies this data as inputs to an artificial neural network.

Abstract: Systems and methods provide a media guidance application that recognizes a plurality of natural language search queries for identifying a set of search results. For example, a user may want to determine when the Yankees are playing their next baseball game. The user may structure their query in multiple ways, such as, “When are the Yankees playing?” “What time is the Yankees game?” “When is the next Yankees baseball game?” The user would expect the same result, a description of when the Yankees are playing, regardless of how the query is structured. The systems and methods enable a user to use a plurality of search queries when searching for items or information to get desired results.

Abstract: Systems and methods are described to address shortcomings in a conventional conversation system via a novel technique utilizing artificial neural networks to train the conversation system whether or not to continue context. In some aspects, an interactive media guidance application determines a type of conversation continuity in a natural language conversation comprising first and second queries. The interactive media guidance application determines a first token in the first query and a second token in the second query. The interactive media guidance application identifies entity data for the first and second tokens. The interactive media guidance application retrieves, from a knowledge graph, graph connections between the entity data for the first and second tokens. The interactive media guidance application applies this data as inputs to an artificial neural network.