Google Inc.

Xuefu Wang

Daniel Joseph Clancy

Simon Tong

Oren Eli Zamir

John Piscitello

Jeffrey M Bartelma

Aitan Weinberg

Adam Mathes

Breen Hagan

Raghavan Manmatha

Gopal Venu Vemula

Sarah Sirajuddin

Eugene Ie

Christopher Richard Uhlik

Luc Vincent

Shalini Agarwal

Bo Pang

Vibhor Nanavati

Xinyu Tang

Bhavesh R Mehta

Angshuman Guha

Charles Chapin

Romain Thibaux

Methods and systems allow users to enter natural language terms that describe a particular web site into an address field of a browser instead of a formal URL. The terms are evaluated to determine whether they correspond, with a high likelihood, to a particular web site. If so, this web site may be immediately accessed. If not, a list of search results based on the terms may be displayed by the browser.

Named URL entry

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, and including a method for providing content. The method comprises receiving a request for content from a user, the request for content being associated with a location and including one or more keywords. The method further comprises determining a prominent entity in proximity to the location and one or more categories associated with the prominent entity. The method further comprises evaluating historical search queries received from the user to determine one or more interests of the user. The method further comprises determining one or more additional keywords based on the evaluating. The method further comprises determining one or more content items based at least in part on the one or more keywords, the categories and the one or more additional keywords. The method further comprises providing the one or more content items responsive to the request.

Interest-based keywords for prominent entity and by location

In general, the subject matter described in this specification can be embodied in methods, systems, and program products for providing a query to a search engine for searching a corpus of documents. A plurality of result documents are received from the search engine, each result document associated with a ranking. For a first document in the plurality, the following is performed. First, a second document in a second corpus is identified as containing content that identifies the same physical object as the first document. The second document was included in a plurality of result documents responsive to a second query of the second corpus, similar to the first query. Second, a new ranking is determined for the first document based on its ranking and relevance data associated with the second document. The relevance data is indicative of the second document's popularity as a result for the second query.

Sharing search engine relevance data

Methods, systems, and apparatus, including computer program products are provided for responding to search queries having results that identify books. In one aspect, a search query and multiple web pages that satisfy the search query and have a ranked order as responses to the search query are received. A subset of web pages that are each a reference page for a respective book are selected. A web page is a reference page for a book when the web page includes a reference to the book and satisfies a citation criterion for the book. A book score is assigned to each of the books for which there is at least one reference page in the group of highest ranking web pages. The book scores are used to select one or more of the books. A book reference is generated for each of the books and the book references are provided in response to the search query.

Providing book information in response to queries

A system, method, and computer program determines section information of a digital volume. Digital volumes include digital representations of human-readable content, such as digitized books. Phrases are extracted from a table of contents of a digital volume. Matching phrases that at least approximately match the extracted phrases are identified in the body of the digital volume. A best matching phrase is determined for each extracted phrase based on the ordering of the extracted phrases and the matching phrases, and based on match scores indicating the quality of the matches. Section information is generated, including section headings and section start locations based on the best matching phrases. The digital volume is presented to users with links from the table of contents to the section headings on the section start pages. The section information is also used to enhance searching of the digital volume by users.

Determining section information of a digital volume

A system identifies metadata associated with a document by capturing text of a document and comparing the text of the document with a collection of metadata records. Sets of matches between the text of the document and at least one record in the collection of metadata records may be identified, where each set of matches corresponds to a metadata record in the collection of metadata records. Metadata records corresponding to each set of matches may be scored. At least one of the metadata records may be identified based on the scores of the metadata records. The at least one identified metadata record may be associated with the document.

Automatic metadata identification

Methods, systems, and apparatus, including computer program products, for generating user identifier profiles. A user identifier profile characterizes a user based on events that occurred during past user sessions for a user (e.g., past online activities). An event is an action that occurs during a user session, such as a web page view, an advertisement click-through, and a conversion. A user identifier profile can be used, for example, to select advertisements targeted to the user. A user identifier profile includes information about inferred user interests and inferred user demographics.

Generating user profiles

A user is associated with profile information indicating a level of interest in a plurality of topic categories. To obtain an advertisement for a preferred category, the client requests advertisements data from two servers. A request to one of the ad servers includes a user preferred category and a number of other categories. A request to the other ad server includes only the other categories. After the servers send advertisements corresponding to the categories in the requests, a difference is determined between the received advertisements, which produces the advertisement for the preferred category. In some embodiments, a single request is made to a server for a number of advertisements, those advertisements corresponding to the user's profile information are provided a higher likelihood of display in accordance with the advertisement's similarity to the user's profile.

Privacy preserving personalized advertisement delivery system and method

Sharing search engine relevance data between corpora

Informational book query

Methods, systems, and apparatus for determining similarity measures between vertical categories based on users' online activities. The similarity measures are symmetric similarity measures based on both a similarity measure of a first vertical category relative to a second vertical category and a similarity measure of the second vertical category relative to the first vertical category.

Category similarities

A user interface (e.g., a browser window) includes a display area for displaying an image (e.g., a book page image). The image can be rescaled based on the dimensions of the display area, one or more attributes of the image and other factors. In some implementations, a sequence of images are searched for a table of contents. If a table of contents does not exist, one is created by searching the images for white space and/or other attributes that can be used to determined entries in the table of contents. The entries in the table of contents can be hypertext links.

Recognizing table of contents in an image sequence

A user interface (e.g., a browser window) includes a display area for displaying a content reference page. In some implementations, a content reference page is generated that includes information related to content. The content reference page includes sections for presenting keywords found in the content, reviews of the content, portions of content that are of interest to a user (or a class of users) and other useful references, etc.

Growing community of inventors

Los Altos, CA, United States of America

Xuefu Wang