A comparison of semantic similarity models in evaluating concept similarity

Q. X. Xu, W. Z. Shi

Research output: Journal article publicationConference articleAcademic researchpeer-review

Abstract

The semantic similarities are important in concept definition, recognition, categorization, interpretation, and integration. Many semantic similarity models have been established to evaluate semantic similarities of objects or/and concepts. To find out the suitability and performance of different models in evaluating concept similarities, we make a comparison of four main types of models in this paper: the geometric model, the feature model, the network model, and the transformational model. Fundamental principles and main characteristics of these models are introduced and compared firstly. Land use and land cover concepts of NLCD92 are employed as examples in the case study. The results demonstrate that correlations between these models are very high for a possible reason that all these models are designed to simulate the similarity judgement of human mind.

Original languageEnglish
Pages (from-to)173-178
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume39
Publication statusPublished - 2012
Event22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012 - Melbourne, Australia
Duration: 25 Aug 20121 Sep 2012

Keywords

  • Concept similarity
  • Feature model
  • Geometric model
  • Network model
  • Semantic similarity
  • Transformational model

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development

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