Google Inc.

Sun Microsystems, Inc.

Benedict A Gomes

Jeffrey Adgate Dean

Sanjay Ghemawat

Krishna Asur Bharat

Georges R Harik

Bay-Wei W Chang

P Pandurang Nayak

Christopher Rohrs

Michael Alex Frumkin

Kushal Dave

David Robert Bailey

Amitabh Singhal

Alexis J Battle

Corin Anderson

Paul Fontes

Othar Hansson

David Robert Black

Ziga Mahkovec

Olcan Sercinoglu

Jon M Wiley

Jonathan James Effrat

Marcin K Wichary

Shashi Seth

Benjamin Thomas Smith

Benjamin J McMahan

Manas Tungare

Xiangtian Dai

Johanna R Wright

Simon Tong

Monika Hildegard Henzinger

David P Marmaros

Michal Cierniak

Michael Stoppelman

Craig Silverstein

Luis Castro

Walt Lin

Avni Stocky

Noam M Shazeer

John Ogden Lamping

Taher H Haveliwala

Boris Weissman

Marissa Ann Mayer

Gautham K Thambidorai

Vineet Gupta

Avni Shah

Mizuki McGrath

Masanori Harada

Gauthaum K Thambidorai

Sergey Brin

Lev Finkelstein

Lars Bak

David P Stoutamire

Matthew D Cutts

Tal Cohen

Ziv Bar-Yossef

Eran Ofek

Gunes Erkan

Robert J Ennals

Oren Naim

Nitsan Oz

Gil Simha Briskin

Martin Farach-Colton

Jonathan David Tang

Eddo Kim

Asaph Arnon

Sreeram Duvvuru

Anna Bendersky

Zvi Ben-Haim

Matan Kalman

Georges R Hank

Benjamin J Mcmahan

A method of presenting computer-generated search result information can include receiving a search request from a client computer; identifying a plurality of search results responsive to the search request; ranking the plurality of search results using content in one or more web notebooks; and providing the ranked plurality of search results for presentation in the client computer. Using the content can include determining whether at least one of a title, a heading, clipped content, metadata or a user-annotation in at least one web notebook relates to the search request and, if so, increasing a ranking of at least one search result referenced by the at least one web notebook.

Presenting search result information

Methods, systems, and apparatus, including computer program products, for processing search query suggestions. In one aspect, a search service provides query suggestions responsive to a query suggestion request from a client device, and determines if a prediction criterion is met. The prediction criterion is independent of a user selection of a query suggestion provided in response to one or more query suggestion requests. In response to determining that the prediction criterion is met, the search system provides search results to the client device. The search results are responsive to one of the query suggestions provided in response to the query suggestion request or one or more previous query suggestion requests.

Predictive query completion and predictive search results

A first search is performed in response to a received search query. The first search is based at least in part on a first portion of the search query. In the first search, a first set of content items are searched over to identify a first set of search results. Each result in the first set of search results identifies at least one content item of the first set of content items. A second set of content items for performing a second search is determined based at least in part on one or more of the results in the first set of search results. The second set of content items includes content items not included in the first set of search results. A second search is performed, searching over the second set of content items to identify a second set of search results. The second search is based at least in part on a second portion of the search query. Each result in the second set of search results identifies at least one content item of the second set of content items.

Performing multiple related searches

A computer-implemented method of determining the relevance, to a user, of documents accessible over a computer network involves analyzing information relating to a first document, identifying a second document corresponding to the first document using a computer, obtaining information that indicates the relevance of a second document, determining the relevance of the first document using the information indicating relevance of the second document. The first document may be a mobile document, while the second may be a non-mobile document.

Mobile to non-mobile document correlation

An information retrieval system includes a query revision architecture that integrates multiple different query revisers, each implementing one or more query revision strategies. A revision server receives a user's query, and interfaces with the various query revisers, each of which generates one or more potential revised queries. The revision server evaluates the potential revised queries, and selects one or more of them to provide to the user. A session-based reviser suggests one or more revised queries, given a first query, by calculating an expected utility for the revised query. The expected utility is calculated as the product of a frequency of occurrence of the query pair and an increase in quality of the revised query over the first query.

Estimating confidence for query revision models

A search engine server system receives from a client system a search query and identifies a set of documents in accordance with the search query. A content snippet corresponding to content in a respective document of the identified set of documents is generated, the content snippet associated with at least one query term of the one or more query terms in the search query. A response to the search query is returned to the client system, the response including information identifying at least the respective document and including the content snippet. Generating the content snippet includes performing a first decompression operation on first token identifiers, from a compressed document repository, to provide a set of second token identifiers, and performing a second decompression operation on the set of second token identifiers to recover uncompressed content comprising a portion of the respective document.

Generating content snippets using a tokenspace repository

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing answer boxes based on query results. One of the methods includes receiving seed queries for an answer box; analyzing query log information, wherein analyzing query log information comprises identifying query results that have been provided in response to the seed queries; identifying one or more of the query results as answer box indicators based on the analyses of the query log information, wherein the answer box indicators are indicators for the answer box; and storing data identifying the one or more query results as answer box indicators for the answer box.

Providing answer boxes based on query results

Methods and apparatus related to identifying authorship of Internet content. Some implementations are directed to methods and apparatus for identifying a content submission form on a webpage, recognizing submission of content by a user via the content submission form, and transmitting verification data in response to submission of the content by the user. The verification data may include content data indicative of at least some of the content submitted for publication via the content submission form.

Systems and methods related to identifying authorship of internet content

A system may aggregate highlighting information associated with a document that includes a number of elements. The highlighting information may identify one or more of the elements that have been highlighted by a group of users. The system may determine weight values for the one or more elements, generate information associated with the document based on the weight values, and provide the information.

Highlighting of document elements

Adjusting search result rankings based on multiple user highlighting of documents

Methods, systems and apparatus are described herein that include obtaining metadata within a document, where the metadata comprises a sequence of terms. Tags are assigned to terms in the sequence of terms based at least in part on grammatical relationships between the terms, thereby forming a corresponding sequence of tags. A determination is made that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags. In response to the determination, the sequence of terms is stored as a query suggestion.

Processing of document metadata for use as query suggestions

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Mountain View, CA, United States of America

Benedict A Gomes