A semi-automatic approach to extracting common sense knowledge from knowledge sources

  • Authors:
  • Veda C. Storey;Vijayan Sugumaran;Yi Ding

  • Affiliations:
  • Department of Computer Information Systems, J. Mack Robinson College of Business, Georgia State University, Atlanta, GA;Department of Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, MI;Department of Computer Information Systems, J. Mack Robinson College of Business, Georgia State University, Atlanta, GA

  • Venue:
  • NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
  • Year:
  • 2005

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Abstract

Common sense knowledge based systems are developed by researchers to enable machines to understand ordinary knowledge and reason intelligently as a human would. The knowledge repositories of such systems are usually developed manually by a knowledge engineer or by users. Building a knowledge base of common sense knowledge such as that possessed by an average human being would be a very time-consuming, if not impossible, task. Some aspects of real world knowledge have already been captured and organized into various repositories such as the World Wide Web, WordNet, and the DAML ontology library. However, the extraction and integration of common sense knowledge from those sources remains a challenge. To address this challenge, an architecture for a Common Sense Knowledge Extractor is proposed that serves as an intermediary tool to extract common sense knowledge from several knowledge sources in order to develop a common sense repository. The design of the system as an extension of prior research on intelligent query processing is presented.