Textwise LLC

Theodore G Diamond

Michael L Weiner

David L Snyder

Elizabeth D Liddy

Woojin Paik

Mary E McKenna

Edmund S Yu

Bhaskaran Balakrishnan

A system and method for improving information retrieval effectiveness by dynamically combining evidence information produced by a plurality of retrieval systems matching alternative representations of queries and documents. The user enters a query and the system generates alternative representations of the query. The system also maintains a collection of documents and corresponding alternative representations of the documents. The system then performs matching between the alternative representations of the query and the corresponding alternative representations of the documents and generates individual matching scores for the alternative representation matches. Correlation information is also determined for the individual scores. The individual matching scores are combined using a dynamic combination regime which is adjusted for the query. The dynamic combination regime may be a function of query specific information, retrieved documents specific information, or correlation information. The documents are ranked based on the combined scores. The user may also mark specific documents as being relevant. This relevance feedback information may also be used to modify the dynamic combination regime.

Information retrieval using dynamic evidence combination

Techniques for generating sophisticated representations of the contents of both queries and documents in a retrieval system by using natural language processing (NLP) techniques to represent, index, and retrieve texts at the multiple levels (e.g., the morphological, lexical, syntactic, semantic, discourse, and pragmatic levels) at which humans construe meaning in writing. The user enters a query and the system processes the query to generate an alternative representation, which includes conceptual-level abstraction and representations based on complex nominals (CNs), proper nouns (PNs), single terms, text structure, and logical make-up of the query, including mandatory terms. After processing the query, the system displays query information to the user, indicating the system's interpretation and representation of the content of the query. The user is then given an opportunity to provide input, in response to which the system modifies the alternative representation of the query. Once the user has provided desired input, the possibly modified representation of the query is matched to the relevant document database, and measures of relevance generated for the documents. A set of documents is presented to the user, who is given an opportunity to select some or all of the documents, typically on the basis of such documents being of particular relevance. The user then initiates the generation of a query representation based on the alternative representations of the selected document(s).

User interface and other enhancements for natural language information

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Syracuse, NY, United States of America

Theodore G Diamond