Aol Inc.

Facebook, Inc.

Summize, Inc.

Other

Microsoft Technology Licensing, LLC

Twitter, Inc.

Gregory Scott Pass

Abdur Chowdhury

Ophir Frieder

Ajaipal Singh Virdy

Gerald Campbell

Harmannus Vandermolen

David C Sobotka

Travis Adam Walker

Dimitre Piskyulev

Justin M Law

John McClean

Amelia P Williams

Kush Sidhu

James Mark Canon

Shawn C Rose

David Pautler

Oliver Cahill

Martin Boyle

Ultan O'Carroll

An example information assessment system includes communication circuitry; storage; and processing circuitry. The processing circuitry is configured to control the information assessment system to at least receive, via the communication circuitry, content from multiple users relating to a particular topic; determine, for the content from each respective user, an orientation value reflecting a sentiment of the content; store, in the storage, the content from the multiple users in association with the orientation values; and in response to receiving a request for information about the particular topic, generate a visual map reflecting the orientation values associated with the content from the multiple users.

System and method for assessing content

An example system and method elicits reviews and opinions from users via an online system or a web crawl. Opinions on topics are processed in real time to determine orientation. Each topic is analyzed sentence by sentence to find a central tendency of user orientation toward a given topic. Automatic topic orientation is used to provide a common comparable rating value between reviewers and potentially other systems on similar topics. Facets of the topics are extracted via a submission/acquisition process to determine the key variables of interest for users.

System and method for evaluating sentiment

A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

Query disambiguation

Expert domains for a query category represent domains from which a high percentage of search results for queries associated with the query category are retrieved. The expert domains are identified by establishing a base statistical model that indicates frequencies of appearance for domains in search results retrieved for queries corresponding to multiple categories. In addition, frequencies of domain appearance are determined for search results retrieved for queries associated with a category. Domains that appear more frequently in the search results corresponding to the category are identified as expert domains for the category. A user may be allowed to customize expert domains related to one or more categories by adding or removing expert domains for the category.

Domain expert search

A search query is submitted to one or more information sources associated with a category of the query. The category of the query is indicated by a query ontology that relates queries to query categories. The information sources represent information sources from which a high percentage of search results for queries associated with the category are retrieved. For instance, the category of the query is identified by identifying categories corresponding to variations of the query, where each variation represents a combination of the terms within the query, and where the categories of the variations are assumed to be the categories of the query. Information sources associated with the query categories are identified, and the query is submitted to the identified information sources. Submitting the query to the identified information sources may cause search results retrieved for the query to more closely reflect search results desired by a user that specified the query.

Query routing

Search results are assigned scores based on visual aspects of surrogate representations of the search results which are to be displayed to a query submitter in a search results summary overview. That is, the surrogate representations are relatively short summaries or excerpts of the search results that may be presented in place of the search results themselves, thus enabling an overview of various search results to be perceived by a user concurrently. The search results are assigned scores based on the presence, position, and form of some or all of the query within the corresponding surrogate representations. The search results may be sorted or filtered based on the assigned scores. Assigning scores to the search results based on visual characteristics of the surrogate representations mimics how a user may assess the relevance of the search results when viewing a search results summary page.

Search fusion

A list of 'hot topics' may be provided to a user to indicate information that is currently popular. A topic may be deemed popular when a large number of search queries related to the topic are entered by users. A search system may receive and analyze an electronic source of published information to determine a reason for why a particular popular topic is popular. If content related to why a particular popular topic is popular exists in multiple electronic sources of published information, text summarization techniques may be used to determine a reason for why the popular topic is popular by from among the multiple electronic sources of published information.

Real time query trends with multi-document summarization

Systems and methods are provided for providing content to be displayed to a user in response to a search request. One embodiment of a method includes identifying a page recipe comprising one or more page properties and one or more content module definitions, each content module definition defining an amount of content to be displayed in a content module to be displayed on a results page, the location of the content module to be displayed on the results page, and a content source from which to obtain content to be displayed in the content module, and using the page recipe to generate a results page to be displayed on a search client.

Dynamically altering search result page layout to increase user response

Search results may be sorted or filtered based on scores assigned to the search results. For example, scores may be assigned to search results based on characteristics of surrogate representations of the search results, which are relatively short summaries or excerpts of the search result that may be presented in place of the search results themselves, and those assigned scores may be used to sort or filter the search results. In one example, pairs of search results may be examined to identify significant drops in quality between search results, which is indicated by a large relative or absolute difference in the scores of the search results. Search results with scores that indicate ranks that are lower than a lower ranked search result of the pair of search results may be eliminated when the difference between the scores assigned to the pair of search results exceeds a maximum allowable difference.

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Reston, VA, United States of America

Gregory Scott Pass