Abstract: Systems and methods are provided for generating for presentation information about an event on a device that is in a mode of operation that prevents presentation of information about events. This may be accomplished by a media guidance application that receives a command, on a user device associated with a first user, to place the user device in a do not disturb mode. The media guidance application receives, while the user device is in the do not disturb mode, information about an event and determines whether the event is relevant to the user. The media guidance application then determines whether the event is trending among a plurality of users associated with the user and, if trending, displays, while the user device is in the do not disturb mode, a notification about the event to the user on the user device.

Abstract: Systems and methods are provided for generating for presentation information about an event on a device that is in a mode of operation that prevents presentation of information about events. This may be accomplished by a media guidance application that receives a command, on a user device associated with a first user, to place the user device in a do not disturb mode. The media guidance application receives, while the user device is in the do not disturb mode, information about an event and determines whether the event is relevant to the user. The media guidance application then determines whether the event is trending among a plurality of users associated with the user and, if trending, displays, while the user device is in the do not disturb mode, a notification about the event to the user on the user device.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user's behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user's behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Methods and systems are provided for generating a response to a natural language query. Specifically, the natural language query is received and a query template that corresponds to the natural language query is determined. One or more search results corresponding to the natural language query are retrieved. One or more attributes associated with a user are selected based on selection criteria. Based on those attributes, a response template previously assigned to the query template is identified. A response to the natural language query is generated based on the identified response template and the retrieved one or more search results.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user’s behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user’s behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Methods and systems are disclosed herein for accurately training a machine learning model with a reduced training data set. A large number of data records may be parsed. Each record may be reduced to a set of symbols representing the composition of each record. A user may assign a classification to each symbol within each record. Records with identical arrangements and classifications of symbols may be grouped together, and a representative sample of data records from each group may be fed into the model as the reduced training data set.

Abstract: In some aspects, control circuitry receives and stores a user-specified time duration to associate with a skip-forward command. When the user later issues a skip-forward command to advance playback of a media asset to a desired location, the control circuitry retrieves the stored time duration, and determines an expected overshoot value associated with the skip-forward command. The control circuitry then compensates for the expected overshoot by calculating a new location in the media asset based on both the retrieved time duration and expected overshoot value. Upon advancing to the new location, the media asset is played back in a fast-forward mode, e.g., at a speed higher than normal speed.

Abstract: In some aspects, control circuitry receives and stores a user-specified time duration to associate with a skip-forward command. When the user later issues a skip-forward command to advance playback of a media asset to a desired location, the control circuitry retrieves the stored time duration, and determines an expected overshoot value associated with the skip-forward command. The control circuitry then compensates for the expected overshoot by calculating a new location in the media asset based on both the retrieved time duration and expected overshoot value. Upon advancing to the new location, the media asset is played back in a fast-forward mode, e.g., at a speed higher than normal speed.

Abstract: In some aspects, control circuitry receives and stores a user-specified time duration to associate with a skip-forward command. When the user later issues a skip-forward command to advance playback of a media asset to a desired location, the control circuitry retrieves the stored time duration, and determines an expected overshoot value associated with the skip-forward command. The control circuitry then compensates for the expected overshoot by calculating a new location in the media asset based on both the retrieved time duration and expected overshoot value. Upon advancing to the new location, the media asset is played back in a fast-forward mode, e.g., at a speed higher than normal speed.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user's behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user's behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user’s behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user’s behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user's behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user's behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Methods and systems are described for a media guidance application that tailors media content recommendations for downloadable content to the current interests of the users. For example, the media guidance application may determine the current interests of a user based on the media content recently consumed by the friends of the user, and automatically download that media content. In such cases, the media guidance application may monitor social networks of the user for indications of media content that may have been recently consumed by the friends of a user as such media content is likely to be of current interest to the user. In response to detecting media content that was recently consumed by the friend of the user, the media guidance application may automatically download the media content to a device of the user.

Abstract: Systems and methods are provided for generating for presentation information about an event on a device that is in a mode of operation that prevents presentation of information about events. This may be accomplished by a media guidance application that receives a command, on a user device associated with a first user, to place the user device in a do not disturb mode. The media guidance application receives, while the user device is in the do not disturb mode, information about an event and determines whether the event is relevant to the user. The media guidance application then determines whether the event is trending among a plurality of users associated with the user and, if trending, displays, while the user device is in the do not disturb mode, a notification about the event to the user on the user device.

Abstract: Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user's behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user's behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Abstract: Methods and systems are disclosed herein for accurately training a machine learning model with a reduced training data set. A large number of data records may be parsed. Each record may be reduced to a set of symbols representing the composition of each record. A user may assign a classification to each symbol within each record. Records with identical arrangements and classifications of symbols may be grouped together, and a representative sample of data records from each group may be fed into the model as the reduced training data set.

Abstract: Methods and systems are described for a media guidance application that tailors media content recommendations for downloadable content to the current interests of the users. For example, the media guidance application may determine the current interests of a user based on the media content recently consumed by the friends of the user, and automatically download that media content. In such cases, the media guidance application may monitor social networks of the user for indications of media content that may have been recently consumed by the friends of a user as such media content is likely to be of current interest to the user. In response to detecting media content that was recently consumed by the friend of the user, the media guidance application may automatically download the media content to a device of the user.

Abstract: Methods and systems are provided for generating a response to a natural language query. Specifically, the natural language query is received and a query template that corresponds to the natural language query is determined. One or more search results corresponding to the natural language query are retrieved. One or more attributes associated with a user are selected based on selection criteria. Based on those attributes, a response template previously assigned to the query template is identified. A response to the natural language query is generated based on the identified response template and the retrieved one or more search results.

Abstract: Systems and methods are provided for generating for presentation information about an event on a device that is in a mode of operation that prevents presentation of information about events. This may be accomplished by a media guidance application that receives a command, on a user device associated with a first user, to place the user device in a do not disturb mode. The media guidance application receives, while the user device is in the do not disturb mode, information about an event and determines whether the event is relevant to the user. The media guidance application then determines whether the event is trending among a plurality of users associated with the user and, if trending, displays, while the user device is in the do not disturb mode, a notification about the event to the user on the user device.

Abstract: Methods and systems are disclosed herein for accurately training a machine learning model with a reduced training data set. A large number of data records may be parsed. Each record may be reduced to a set of symbols representing the composition of each record. A user may assign a classification to each symbol within each record. Records with identical arrangements and classifications of symbols may be grouped together, and a representative sample of data records from each group may be fed into the model as the reduced training data set.