Google Inc.

Apple Inc.

Laserlike, Inc.

Anand Shukla

Vishnu Priya Natchu

Krishna Asur Bharat

Mark E Pearson

Kushal Tayal

Stefan Buettcher

Srinivasan Venkatachary

Steven D Baker

Pavan Kumar Desikan

Salvatore J Candido

Isabelle L Stanton

Derek Kisman

Techniques for providing an enhanced search to generate a feed based on a user's interests are disclosed. In some embodiments, a system/process/computer program product for providing an enhanced search to generate a feed based on a user's interests includes receiving a plurality of interests associated with a user, searching online content including one or more websites (e.g., news or other content websites, social networking sites, and/or other online content) based on the plurality of interests associated with the user, receiving a plurality of web documents (e.g., links to websites, social networking sites, and other online content) based on the search for online content, ranking the plurality of web documents based on a document score and a user signal, and generating a content feed that includes at least a subset of the plurality of web documents based on the ranking.

Enhanced search to generate a feed based on a user's interests

An embedding associated with a query comprising one or more query terms is determined to be not stored in memory. An embedding is generated for the one or more query terms. One or more web documents that are similar to the generated embedding are determined. One or more content cards associated with the one or more web documents that are determined to be similar to the generated embedding are provided in a content feed.

Golden embeddings

A set of documents associated with a query comprising one or more query terms is determined. A subset of the documents is sampled to identify a corresponding query constraint pattern associated with each document included in the subset of the documents. An entry of an inverted index is generated based on the corresponding query constraint pattern associated with each document included in the subset of document.

Query pattern matching

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing actions of determining that one or more in-depth article search results are to be provided in response to a query, obtaining a topicality score for each in-depth article of a plurality of in-depth articles, each topicality score indicating a degree of relevance of a respective in-depth article to the query, obtaining a document score for each in-depth article of the plurality of in-depth article, each document score being based on a respective topicality score and a respective in-depth article score, selecting one or more in-depth articles from the plurality of in-depth articles based on respective document scores, and providing the one or more in-depth article search results for display, each in-depth article search result representing an in-depth article of the one or more in-depth articles.

Surfacing in-depth articles in search results

Methods, systems, and apparatus, including computer program products, for generating or using augmentation queries. In one aspect, a first query stored in a query log is identified and a quality signal related to the performance of the first query is compared to a performance threshold. The first query is stored in an augmentation query data store if the quality signal indicates that the first query exceeds a performance threshold.

Query augmentation

Methods, systems, and apparatus, including computer program products, for generating or using augmentation queries. In one aspect, augmentation queries are identified from user interactions or are machine generated. The augmentation queries can be stored in an augmentation query data store. When a user submits a search query to a search engine, the terms of the query, and optionally additional information, such as the geographic location from which the query is received or the language of the query, can be used to identify stored augmentation queries and select one or more similar augmentation queries. The selected augmentation queries, in turn, can be used by the search engine perform an augmented search operation.

Growing community of inventors

Santa Clara, CA, United States of America

Anand Shukla