Abstract: Systems, methods, and computer-readable storage media are provided for capturing a state of a user interface. A state of the user interface presented by an application is identified, the user interface comprising a plurality of user interface elements. An indication of a modification to the user interface or an indication of user activity is received, where the indication of user activity is associated with one of the plurality of user interface elements. The state of the user interface is modified based on at least one of the indication of a modification to the user interface or user activity.

Abstract: Examples of the present disclosure describe systems and methods of identifying good and bad abandonment using gesture movement. In aspects, user feedback signals may be received by a client device in response to the viewing and/or navigation of query results. The feedback signals may be provided to a framework for determining and/or analyzing query abandonment. The framework may identify gesture data in the feedback signals and extract feature data from the gesture data. The feature data may be provided to a metrics component to determine metrics and/or satisfaction values for the feature data. The metrics and/or feature data may be used to train a predictive model to identify good abandonment in query results.

Abstract: Systems, methods, and computer-readable storage media are provided for capturing a state of a user interface. A state of the user interface presented by an application is identified, the user interface comprising a plurality of user interface elements. An indication of a modification to the user interface or an indication of user activity is received, where the indication of user activity is associated with one of the plurality of user interface elements. The state of the user interface is modified based on at least one of the indication of a modification to the user interface or user activity.

Abstract: Examples of the present disclosure describe systems and methods of identifying good and bad abandonment using gesture movement. In aspects, user feedback signals may be received by a client device in response to the viewing and/or navigation of query results. The feedback signals may be provided to a framework for determining and/or analyzing query abandonment. The framework may identify gesture data in the feedback signals and extract feature data from the gesture data. The feature data may be provided to a metrics component to determine metrics and/or satisfaction values for the feature data. The metrics and/or feature data may be used to train a predictive model to identify good abandonment in query results.

Abstract: Architecture that operates in combination with an integrated search framework to derive user intent associated with a search query, and then based on the derived intent, choose the search method: a local search on the current local device from which the search is initiated, a non-local search of data sources other than the local device, or both the local search and the non-local search. The query context can be derived to more effectively assess the query intent. The architecture employs predictive models trained with candidate features that enable the prediction of a singular intent (or degree of intent) in the integrated search environment. The models can be trained using historical and real-time features. A classifier is trained using the features. The user intent is then derived based on the classifier output and the search is performed accordingly.

Abstract: Examples of the present disclosure describe systems and methods for improving the recommendations provided to a user by a recommendation system using viewed content as implicit feedback. In some aspects, attention models are created/updated to infer the user attention of a user that has viewed or is viewing content on a computing device. The attention model may be used to convert inferences of user attention into inferences of user satisfaction with the viewed content. The inferences of user satisfaction may be used to generate inferences of fatigue with the viewed content. The inferences of user satisfaction and inferences of user fatigue may then be used as implicit feedback to improve the content selection, content triggering and/or content presentation by the recommendation system. Other examples are also described.

Abstract: Methods are provided for re-ranking documents based on user-specific features. Search results are received from a non-contextual ranking system such that the search results are not specific toward a particular user, such as the user who submitted the search query. Contextual signals are received and provide user-specific features that are used to re-rank documents so that the most important and relevant documents are listed at the top of the list of search results. Each of the user-specific features are evaluated and compared to determine a new position of each document. A set of contextual search results is then generated based on the new positions.

Abstract: Methods are provided for re-ranking documents based on user-specific features. Search results are received from a non-contextual ranking system such that the search results are not specific toward a particular user, such as the user who submitted the search query. Contextual signals are received and provide user-specific features that are used to re-rank documents so that the most important and relevant documents are listed at the top of the list of search results. Each of the user-specific features are evaluated and compared to determine a new position of each document. A set of contextual search results is then generated based on the new positions.

Abstract: Methods and computer-readable media are provided for improving the efficiency of the interleaving process. Once it is determined that a search query is to be used in an interleaving experiment, a primary ranking system and a secondary ranking system are analyzed to determine whether their respective search results for that search query would be identical. If the search results would be identical, the search query is routed only to the primary ranking system and not the secondary ranking system. If, however, it is determined that the search results would not be identical, both the primary ranking system and the secondary ranking system receive the search query for processing.

Abstract: Methods and computer-readable media are provided for improving the efficiency of the interleaving process. Once it is determined that a search query is to be used in an interleaving experiment, a primary ranking system and a secondary ranking system are analyzed to determine whether their respective search results for that search query would be identical. If the search results would be identical, the search query is routed only to the primary ranking system and not the secondary ranking system. If, however, it is determined that the search results would not be identical, both the primary ranking system and the secondary ranking system receive the search query for processing.