Combining ICS semantic factor into concept similarity evaluating based on RFCA

Chongyang Shi*, Zhendong Niu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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 Tverskya̧ŕs similarity model.

Original languageEnglish
Title of host publicationiiWAS2009 - The 11th International Conference on Information Integration and Web-based Applications and Services
Pages502-506
Number of pages5
DOIs
Publication statusPublished - 2009
Event11th International Conference on Information Integration and Web-based Applications and Services, iiWAS2009 - Kuala Lumpur, Malaysia
Duration: 14 Dec 200916 Dec 2009

Publication series

NameiiWAS2009 - The 11th International Conference on Information Integration and Web-based Applications and Services

Conference

Conference11th International Conference on Information Integration and Web-based Applications and Services, iiWAS2009
Country/TerritoryMalaysia
CityKuala Lumpur
Period14/12/0916/12/09

Keywords

  • concept lattice
  • formal context
  • information content similarity
  • rough set

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