MARY B MCKENNA, PTA
Restorative Service Providers at Fay Rd, Syracuse, NY

6026388, Feb 15, 2000

Aug 14, 1996

8/696702

Elizabeth D. Liddy - Syracuse NY
Woojin Paik - Syracuse NY
Mary E. McKenna - Syracuse NY
Michael L. Weiner - Webster NY
Edmund S. Yu - DeWitt NY
Theodore G. Diamond - Mercer Island WA
Bhaskaran Balakrishnan - Syracuse NY
David L. Snyder - Pittsford NY

Textwise, LLC - Syracuse NY

G06F 1730

707 1

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.

5963940, Oct 5, 1999

Aug 14, 1996

8/698472

Elizabeth D. Liddy - Syracuse NY
Woojin Paik - Syracuse NY
Mary E. McKenna - Syracuse NY
Ming Li - Jersey City NJ

Syracuse University - Syracuse NY

G06F 1730

707 5

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.