Abstract: Methods and systems for presenting contextually relevant push content when a user is passively engaged with an application are described herein. The system detects that the user is engaged with an application on a device and monitors the user's level of engagement with the application. If the system determines that the user is passively engaged, the system prepares to insert push content into the current output. The system identifies a region on the current output into which to insert push content, for example a region unoccupied by content or a particular object. The system identifies a context of the current output and selects a push content item based on the context of the current output. Then, the system inserts the push content item into the empty region on the current output.

Abstract: Systems and associated methods are described for providing content recommendations. The system accesses a plurality of recommendation algorithms and assigns a plurality of weight values to each prediction algorithm. Then, the system generates a set of candidate weight combinations, such that each candidate combination includes a weight value assigned to each prediction algorithm. Then requests for content items are received over a predetermined period of time. For each combination, the system generates a set of recommended content items and an evaluation metric that is based on matches with requests. Afterwards, the system replaces a candidate combination that resulted in a generation of a lowest evaluation metric. The aforementioned steps are repeated until the evaluation metrics stop improving. Then display identifiers are displayed for a set of recommended content items generated for a candidate combination with the highest evaluation metric.

Abstract: Methods and systems for presenting contextually relevant push content when a user is passively engaged with an application are described herein. The system detects that the user is engaged with an application on a device and monitors the user's level of engagement with the application. If the system determines that the user is passively engaged, the system prepares to insert push content into the current output. The system identifies a region on the current output into which to insert push content, for example a region unoccupied by content or a particular object. The system identifies a context of the current output and selects a push content item based on the context of the current output. Then, the system inserts the push content item into the empty region on the current output.

Abstract: Systems and associated methods are described for providing content recommendations. The system accesses a plurality of recommendation algorithms and assigns a plurality of weight values to each prediction algorithm. Then, the system generates a set of candidate weight combinations, such that each candidate combination includes a weight value assigned to each prediction algorithm. Then requests for content items are received over a predetermined period of time. For each combination, the system generates a set of recommended content items and an evaluation metric that is based on matches with requests. Afterwards, the system replaces a candidate combination that resulted in a generation of a lowest evaluation metric. The aforementioned steps are repeated until the evaluation metrics stop improving. Then display identifiers are displayed for a set of recommended content items generated for a candidate combination with the highest evaluation metric.

Abstract: Methods and systems for inserting a push content item into a user display are described herein. The system identifies an object on a current output of an application on a device. The system also selects a push content item comprising an animatable graphic element from a database of push content. The system inserts the push content item at an insertion point in the current output and animates the animatable graphic element on the current output of the application. The system also causes at least one interaction of the animatable graphic element with the object on the current output of the application.

Abstract: Methods and systems for determining a type of push content to display to a user are described herein. The system identifies a context of a current output of an application on a device. The system extracts user profile information from a user profile of the user. The system then selects a type of push content from a database of types of push content based on the user profile information and the context of the current output. Finally, the system inserts a push content item of the selected type into the current output of the application.

Abstract: Methods and systems for inserting a push content item into a user display are described herein. The system identifies an object on a current output of an application on a device. The system also selects a push content item comprising an animatable graphic element from a database of push content. The system inserts the push content item at an insertion point in the current output and animates the animatable graphic element on the current output of the application. The system also causes at least one interaction of the animatable graphic element with the object on the current output of the application.

Abstract: Methods and systems for presenting contextually relevant push content when a user is passively engaged with an application are described herein. The system detects that the user is engaged with an application on a device and monitors the user's level of engagement with the application. If the system determines that the user is passively engaged, the system prepares to insert push content into the current output. The system identifies a region on the current output into which to insert push content, for example a region unoccupied by content or a particular object. The system identifies a context of the current output and selects a push content item based on the context of the current output. Then, the system inserts the push content item into the empty region on the current output.

Abstract: Systems and associated methods are described for providing content recommendations. The system accesses a plurality of recommendation algorithms and assigns a plurality of weight values to each prediction algorithm. Then, the system generates a set of candidate weight combinations, such that each candidate combination includes a weight value assigned to each prediction algorithm. Then requests for content items are received over a predetermined period of time. For each combination, the system generates a set of recommended content items and an evaluation metric that is based on matches with requests. Afterwards, the system replaces a candidate combination that resulted in a generation of a lowest evaluation metric. The aforementioned steps are repeated until the evaluation metrics stop improving. Then display identifiers are displayed for a set of recommended content items generated for a candidate combination with the highest evaluation metric.