Combining ICS semantic factor into concept similarity evaluating based on RFCA

  • Authors:
  • Chongyang Shi;Zhendong Niu

  • Affiliations:
  • Beijing Institute of Technology, Beijing, P.R. China;Beijing Institute of Technology, Beijing, P.R. China

  • Venue:
  • Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
  • Year:
  • 2009

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Abstract

In this paper, a novel similarity measuring method based on Rough Formal Concept Analysis (RFCA) and information content similarity(ICS) is proposed which evaluates the similarity degree between the concepts. We use the information content approach to automatically obtain part of similarity scores of two concepts which makes up the normal featural and structural evaluating model. Thus the similarity of two concepts can be directly calculated from the lower object approximations and lower attribute approximations based on the RFCA and ICS. Consequently the proposed method combines semantic, featural and structural information into decision which can be viewed as the development of Tverskyąrs similarity model.