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Automated knowledge derivation: Domain‐independent techniques for domain‐restricted text sources
Author(s) -
Boggess Lois,
Hodges Julia,
Cordova Jose
Publication year - 1995
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550101003
Subject(s) - computer science , knowledge base , domain knowledge , natural language processing , domain (mathematical analysis) , vocabulary , knowledge extraction , grammar , knowledge based systems , general knowledge , artificial intelligence , object (grammar) , information retrieval , natural language , information extraction , linguistics , mathematics , psychology , mathematical analysis , social psychology , philosophy
This article provides a description of the major components of a system that builds and updates a knowledge base by extracting the knowledge from natural language text. the knowledge extraction is done in a domain‐independent manner and does not rely on particular vocabulary or grammar constructions. the only restriction is that the input text must be technical text from some specific problem domain. an important capability of the system is that it can bootstrap itself. That is, beginning with only a description of the types of object and relationships to be stored in the knowledge base, the system can start with an empty knowledge base and build the knowledge base as it processes the text. the knowledge extraction system's success in extracting knowledge from various input texts was evaluated using scoring metrics reported by Lehnert and Sundheim [ AI Mag ., 12(3) , 81–94 (1991)]. the initial results indicate that the knowledge extraction mechanism is both effective and independent of a particular author's writing style or a particular domain. © 1995 John Wiley & Sons, Inc.