Google Inc.

Mangesh Gupte

Nitin Kumar Gupta

Renshen Wang

Kumar Mayur Thakur

Methods and apparatus related to identifying a query template that includes one or more terms and a member of an entity category and ranking the query template. Query suggestions may be determined based on the query template. The ranking of the query template may be utilized to determine if the query template is a valid query template. The ranking of the template may be based on at least a count of occurrences of one or more of the entities of the entity category in past queries that conform to the query template.

Query suggestion templates

Methods and apparatus for determining whether query templates that have the same entity collection identifier are semantically equivalent query templates based on determining a similarity measure between the query templates. The similarity measure may be based on various factors. For example, in some implementations the similarity measure may be based on a number of the entities of the entity collection that instantiate both of the query templates in a record of past user queries. Also, for example, in some implementations the similarity measure may be based on a number of the entities of the entity collection that instantiate both of the query templates in a record of past user queries and are determined to be entities that satisfy a threshold level of entity similarity between the query templates. In some implementations, terms of two query templates that are determined to be equivalent may be determined to be synonymous.

Semantically equivalent query templates

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, from computer-readable memory, a particular item of digital content distributed by a user through a computer-implemented social networking service; identifying, using the one or more processors, a set of items of digital content distributed by the user through the computer-implemented social networking service; receiving interaction data from the computer-readable memory; determining, based on the received interaction data, at least one of a user ranking score associated with the user and an item ranking score associated with the particular item of digital content; and storing the at least one of the user ranking score and the item ranking score in the computer-readable memory.

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Sunnyvale, CA, United States of America

Mangesh Gupte