Google Inc.

Apple Inc.

International Business Machines Corporation

Netscape Communications Corporation

New Aurora Corporation

Ramanathan V Guha

Patrick F Riley

Vineet Gupta

Andrew Stephen Tomkins

Vivek Raghunathan

Ramakrishnan Srikant

Andrew M Dai

Kiran S Panesar

Pablo Bellver

Aparna Chennapragada

Amay Nitin Champaneria

Frederick Peter Brewin

Mahesh Keralapura Manjunatha

Carolyn F Au

Karthik Lakshminarayanan

Carl Lischeske

Ravi Kolluri

Daniel Gruhl

Corin Anderson

Shanmugasundaram Ravikumar

Othar Hansson

Matthew D Wytock

Dandapani Sivakumar

Vinay Goel

Rahul S Kulkarni

Tania Bedrax-Weiss

Jasmine Novak

David Hyatt

Siddartha Naidu

Vrishali Wagle

Subramanya Srikanth Belwadi

Shivakumar Venkataraman

Gokay Baris Gultekin

Ronald Fagin

Nicholas Brock Weininger

Phokion Kolaitis

Abhinav Jalan

Pradnya Karbhari

Garg Ashutosh

Methods and apparatus for providing travel-related information for a location to a user based on activity indications of the user that are related to the location. The location may be determined based on a set of one or more related activity indications and a travel-related score may be determined for the location that is indicative of likelihood that the user has interest in travelling to the location. The user may be provided the travel-related information for the location based on the travel-related score.

Automatic continued search

A search engine system provides search results that are ranked according to a measure of the trust associated with entities that have provided labels for the documents in the search results. A search engine receives a query and selects documents relevant to the query. The search engine also determines labels associated with selected documents, and the trust ranks of the entities that provided the labels. The trust ranks are used to determine trust factors for the respective documents. The trust factors are used to adjust information retrieval scores of the documents. The search results are then ranked based on the adjusted information retrieval scores.

Search result ranking based on trust

In one implementation, a method for providing information to computer users includes receiving at a server system an indicator of an action performed on a third-party website by a first user of a social network of users. The method can also include creating by the server system first promotional information based upon the received indicator and information associated with the first user of the social network. The method can further include persistently storing by the server system the created first promotional information in a repository of promotional information, wherein the repository stores promotional information associated with a plurality of third-party websites for display to users of a plurality of social networks. The method can additionally include receiving at the server system a request for promotional information to display to a second user of the social network, the second user having an acquaintance relationship with the first user.

Propagating promotional information on a social network

The present invention provides systems and methods for generating alerts based on results received from one or more custom search engines. In an embodiment, the present invention generates alerts based on custom search engines by (1) receiving one or more alert specifications including a custom search engine identifier; (2) receiving at least one current result from the identified custom search engines; (3) determining one or more itemized alert elements based on the at least one current result; and (4) transmitting a signal representing the one or more itemized alert elements to a user via a communication network.

Customized web summaries and alerts based on custom search engines

This invention relates to determining page elements to display in response to a search. A method embodiment of this invention determines a page element based on a search result. The method includes: (1) determining a set of result classifications based on the search result, wherein each result classification includes a result category and a result score; and (2) determining the page element based on the set of result classifications. In this way, a classification is determined based on a search result and page elements are generated based on the classification. By using the search result, as opposed to just the query, page elements are generated that corresponds to a predominant interpretation of the user's query within the search results. As result, the page elements may, in most cases, accurately reflect the user's intent.

Classifying search results

A programmable search engine system is programmable by a variety of different entities, such as client devices and vertical content sites to customize search results for users. Context files store instructions for controlling the operations of the programmable search engine. The context files are processed by various context processors, which use the instructions therein to provide various pre-processing, post-processing, and search engine control operations.

Programmable search engine

A user can issue a query on a search host site. The search host can construct a corresponding reference to custom search engine (CSE) with a URL pointing to a site with information for a CSE specification. The search host sends the reference to a CSE provider and the CSE provider dynamically generates the CSE specification based on the reference. The CSE provider then conducts a search and processes search results accordingly. The processed search results are sent to the search host who outputs the search results for the user. The information for the CSE specification can be stored anywhere accessible in a computer network and can be stored in various formats. Any number of CSE specifications can be automatically generated on demand corresponding to different queries or content requests on the search host site.

Dynamic specification of custom search engines at query-time, and applications thereof

Search results are generated using aggregated context data from two or more contexts. When two or more programmable search engines relate to a similar topic, context data associated with the programmable search engines are aggregated. The context is then applied to a query in order to present, in an integrated manner, relevant search results that make use of context intelligence from more than one programmable search engine.

Aggregating context data for programmable search engines

Growing community of inventors

Los Altos, CA, United States of America

Ramanathan V Guha