Microsoft Technology Licensing, LLC

Exiger Canada, Inc.

Outside Intelligence, Inc.

Daniel Ryan Adamson

Alain Thierry Rappaport

Leo Li-Hong Shih

Victor Fernandovich Comas Lijachev

Timothy Byung Choe

A method for classifying information sources and content based on credibility, reliability, or trust. A content item describing an event is retrieved from an information provider and parsed for links. Each link is evaluated and attributed a sentiment score. The same event is identified in a set of know sources and an event score is calculated based on the credibility of each of the known sources. Finally, the content item is ranked based on the event and sentiment scores.

Method and system for scoring credibility of information sources

In one example, documents that are examined by a search process may be scored in a manner that is specific to a domain. A domain may be a substantive area, such as medicine, sports, etc. Different scoring approaches that take aspects of the domain into account may be applied to the documents, thereby producing different scores than might have been produced by a simple comparison of the terms in the query with the terms in the documents. These domain-based approaches may take a query into account in scoring the documents, or may be query-independent. Each approach may be implemented by a scorer. The combined output of the scorers may be used to generate a score for each document. Documents then may be ranked based on the scores, and search results may be provided.

Domain-based ranking in document search

A method for content extraction and modeling by a computer system for incorporating the content into a domain model including the steps of extracting by an acquisition module content stored on a computer readable medium of at least one data source, determining whether the content is structured or unstructured; wherein structured content has a first content model associated therewith defining at least a format of the structured content and unstructured content has no model associated therewith. Upon a condition in which the content is structured, incorporating the structured content into the domain model; and, upon a condition in which the content is unstructured, determining by the computer system a second content model to transform the unstructured content into newly structured content and incorporating the newly structured content into the domain model.

Method and system for aggregate content modeling

A modeling system enriched with information from a single source (or multiple sources) that allows for the intelligent extension, formulation or reformulation of a request into various processes including but not limited to transmission, discovery, notification, searching, filtering and storing processes is provided. The innovation builds a network of connected information in a specific domain (or group of domains). Additionally, the system enhances the quality and specificity of the results for queries made in various systems including, but not limited to, search engines.

Domain knowledge-assisted information processing

A computer system that facilitates presentation of data to a user. A search engine component receives and executes queries on behalf of a user. Results of the query are received and analyzed by an analysis component that filters and organizes the results as a function of relevancy of the data to the user and associated context of the query. A user interface component presents the data to the user in a manner that facilitates easy consumption/processing of data by respective users. The user interface component can dynamically modify display settings as a function of content and type of information displayed, user state, user preferences, explicit or implicit learning, user intent, etc.

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Toronto, Canada

Daniel Ryan Adamson