SEMANTIC SEARCH OF INFORMATION DATABASES

THIS RESEARCH WILL DEVELOP A METHODOLOGY FOR UTILIZING A LEXICAL DATABASE IN A STATISTICAL RETRIEVAL MODEL TO IMPROVE RETRIEVAL PERFORMANCE (I.E., RECALL AND PRECISION). THE SESAME ARCHITECTURE PROPOSED IN THIS PROPOSAL WILL UTILIZE THE LEXICAL DATABASE IN FOUR MAJOR PHASES OF RETRIEVAL: (1) DOCUMENT ANALYSIS; (2) QUERY FORMULATION; (3) RETRIEVAL AND RANKING; AND (4) QUERY REFORMULATION. A PROTOTYPE WILL BE BUILT TO VERIFY THE EFFECTIVENESS OF SESAME USING A SET OF DOCUMENT DATABASES DEVELOPED AT THE CORNELL UNIVERSITY. WORDNET, A LARGE LEXICAL DATABASE DEVELOPED AT PRINCETON UNIVERSITY, WILL BE USED IN THIS PROJECT. THE ANTICIPATED BENEFIT IS A METHODOLOGY WHICH WILL IMPROVE THE EFFECTIVENESS OF METHODS BASED ON PURELY BOOLEAN KEYWORD SEARCH OR THE STATISTICAL MODEL. IN THE PHASE I RESEARCH, THE METHODOLOGY WILL BE DEVELOPED AND A PROTOTYPE WILL BE BUILT. THE RESULTS FROM THIS RESEARCH WILL HAVE HUGE MARKET POTENTIAL IN PERSONAL INFORMATION MANAGEMENT SYSTEMS, OFFICE INFORMATION SYSTEMS, LIBRARY SYSTEMS, AND WIDE-AREA INFORMATION SERVERS.