Information extraction based multiple-category document classification for the global legal information network

Authors:
Richard D. Holowczak;Nabil R. Adam
Affiliations:
Rutgers University, Center for Information Management, Integration and Connectivity, Newark, NJ;Rutgers University, Center for Information Management, Integration and Connectivity, Newark, NJ
Venue:
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Year:
1997

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Abstract

This paper describes a prototype application of an information extraction (IE) based document classification system in the international law domain. IE is used to determine if a set of concepts for a class are present in a document. The syntactic and semantic constraints that must be satisfied to make this determination are derived automatically from a training corpus. A collection of IE systems are arranged in a classification hierarchy and novel documents are guided down the hierarchy based on the results from the previous level. Experimental results for a research prototype are given on a subset of the Global Legal Information Network domain.