Google Inc.

David Faden

Yew Jin Lim

James A Kunz

Joseph Garrett Linn

William Zhang

Mario Tanev

Charles Jordan Gilliland

Lauren Koepnick

Sagar Gandhi

Sanjit Jhala

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that identify and issue search queries expected to be issued in the future. A set of search queries that have been issued by multiple user devices can be obtained. For each query instance, contextual data can be obtained. A first query and its contextual data can be input to a model that outputs the query's likelihood of being issued in the future. The model can be trained using contextual data for training queries and a corresponding labels for the training queries. The learning model outputs the first query's likelihood of being issued in future, and this query is stored as a repeatable query if the likelihood satisfying a repeatability threshold. Subsequently, a stored repeatable query is issued upon a selection of a user selectable interface component and the search engine provides search results for the query.

Identification and issuance of repeatable queries

A computing system is described that identifies, based on search histories associated with a group of computing devices for a particular context, a task performed by users of the group of computing devices for the particular context. The computing system determines a first degree of likelihood of the task being performed by the users of the group of computing devices for the particular context and determines a second degree of likelihood of the task being performed by the users of the group of computing devices for a broader context that includes the particular context and at least one other context. Responsive to determining that the first degree of likelihood exceeds the second degree of likelihood by a threshold amount, and that a current context of a particular computing device corresponds to the particular context, the computing system transmits, to the particular computing device, information for completing the task for the particular context.

Predicting user needs for a particular context

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Mountain View, CA, United States of America

David Faden