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Leveraging Cyc for IAA

Authors :
VERIDIAN ENGINEERING INC BUFFALO NY
Neal, Jeanette
Rode, Benjamin
Crowner, Chris
Gunning, Dave
Gucwa, John
VERIDIAN ENGINEERING INC BUFFALO NY
Neal, Jeanette
Rode, Benjamin
Crowner, Chris
Gunning, Dave
Gucwa, John
Source :
DTIC AND NTIS
Publication Year :
2002

Abstract

This final technical report summarizes research conducted by Veridian Engineering and Cycorp, Inc. to assess the feasibility of leveraging the combined capabilities of the Intelligence Analyst Associate (IAA), an information extraction (IE) system, and the Cyc Knowledge Base (KB), a very large knowledge base, for monitoring domains of interest to intelligence analysts This research examined mechanisms to help alleviate the textual data overload that intelligence analysts experience. The IAA system has capabilities for processing large volumes of unstructured text, extracting information relevant to intelligence analysts, such as entities and simple events, storing the extracted information in a structured database, and enabling the use of analysis and visualization tools. By utilizing the Cyc KB, more intelligent processing using the context of the documents and that of the analysts' persistent knowledge bases to automatically generate new information and knowledge was accomplished. The inheritance feature of the Cyc KB ontological hierarchies provides a strong benefit in the efficient representation of knowledge. It was also shown that many of the information extraction tasks have interdependencies and that there is an advantage to accomplishing them in a KE using inference.

Details

Database :
OAIster
Journal :
DTIC AND NTIS
Notes :
text/html, English
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn831788569
Document Type :
Electronic Resource