Microsoft Technology Licensing, LLC

University of Washington

Michele Banko

Oren Etzioni

Michael J Cafarella

Lucretia Henrica Vanderwende

Paul Baecke

Peter Richard Bailey

Aurl A Menezes

Systems, methods, and computer-readable storage media for providing query-completion suggestions that include answers to the complete queries suggested while the user is formulating a search query. At least a portion of a search query is received by the search engine. As the portion of the search query is received, query-completion suggestions are identified and answers to the plausible search query completions are identified for inclusion in the search input area. Upon selection of a query-completion suggestion, the search engine results page is presented, wherein the search engine results page includes the answers in the snippets generated for the results that contain the answers to the completed queries suggested to the user.

Coherent question answering in search results

To implement open information extraction, a new extraction paradigm has been developed in which a system makes a single data-driven pass over a corpus of text, extracting a large set of relational tuples without requiring any human input. Using training data, a Self-Supervised Learner employs a parser and heuristics to determine criteria that will be used by an extraction classifier (or other ranking model) for evaluating the trustworthiness of candidate tuples that have been extracted from the corpus of text, by applying heuristics to the corpus of text. The classifier retains tuples with a sufficiently high probability of being trustworthy. A redundancy-based assessor assigns a probability to each retained tuple to indicate a likelihood that the retained tuple is an actual instance of a relationship between a plurality of objects comprising the retained tuple. The retained tuples comprise an extraction graph that can be queried for information.

Open information extraction from the web

Open information extraction from the Web

The present invention is a method and system for identifying words, text fragments, or concepts of interest in a corpus of text. A graph is built which covers the corpus of text. The graph includes nodes and links, where nodes represent a word or a concept and links between the nodes represent directed relation names. A score is then computed for each node in the graph. Scores can also be computed for larger sub-graph portions of the graph (such as tuples) The scores are used to identify desired sub-graph portions of the graph, those sub-graph portions being referred to as graph fragments.

Method and system for ranking words and concepts in a text using graph-based ranking

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Seattle, WA, United States of America

Michele Banko