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Title: A comparison of semantic similarity models in evaluating concept similarity
Authors: Xu, QX 
Shi, WZ 
Issue Date: 1-Aug-2012
Source: International archives of the photogrammetry, remote sensing and spatial information sciences, 1 Aug. 2012, v. XXXIX-B2, p. 173-178
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.
Keywords: Semantic similarity
Concept similarity
Geometric model
Feature model
Network model
Transformational model
Publisher: International Congress for Photogrammetry and Remote Sensing
Journal: International archives of the photogrammetry, remote sensing and spatial information sciences 
ISSN: 1682-1750
EISSN: 2194-9034
DOI: 10.5194/isprsarchives-XXXIX-B2-173-2012
Description: 22nd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing, Aug 25-Sep 01, 2012, Melbourne, Australia
Rights: © Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License (
The following publication Xu, Q. X. and Shi, W. Z.: A COMPARISON OF SEMANTIC SIMILARITY MODELS IN EVALUATING CONCEPT SIMILARITY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B2, 173–178, 2012 is available at
Appears in Collections:Conference Paper

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