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Comparing Geospatial Entity Classes: An Asymmetric and Context-Dependent Similarity Measure (2004)
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| Venue: | International Journal of Geographical Information Science |
| Citations: | 59 - 1 self |
BibTeX
@ARTICLE{Rodríguez04comparinggeospatial,
author = {M. Andrea Rodríguez and Max J. Egenhofer},
title = {Comparing Geospatial Entity Classes: An Asymmetric and Context-Dependent Similarity Measure},
journal = {International Journal of Geographical Information Science},
year = {2004},
volume = {18},
pages = {229--256}
}
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Abstract
Semantic similarity plays an important role in geographic information systems as it supports the identification of objects that are conceptually close, but not identical. Similarity assessments are particularly important for retrieval of geospatial data in such settings as digital libraries, heterogeneous databases, and the World Wide Web. Although some computational models for semantic similarity assessment exist, these models are typically limited by their inability to handle such important cognitive properties of similarity judgments as their inherent asymmetry and their dependence on context. This paper defines the Matching-Distance Similarity Measure (MDSM) for determining semantic similarity among spatial entity classes, taking into account the distinguishing features of these classes (parts, functions, and attributes) and their semantic interrelations (is-a and part-whole relations). A matching process is combined with a semantic-distance calculation to obtain asymmetric values of similarity that depend on the degree of generalization of entity classes. MDSM's matching process is also driven by contextual considerations, where the context determines the relative importance of distinguishing features. Based on a human-subject experiment, MDSM results correlate well with people's judgments of similarity. When contextual information is used for determining the importance of distinguishing features, this correlation increases; however, the major component of the correlation between MDSM results and people's judgments is due to a detailed definition of entity classes.
Keyphrases
context-dependent similarity measure geospatial entity class mdsm result entity class semantic similarity semantic similarity assessment exist contextual consideration inherent asymmetry contextual information computational model matching-distance similarity measure world wide web human-subject experiment asymmetric value important cognitive property geographic information system semantic interrelation important role similarity assessment major component similarity judgment distinguishing feature part-whole relation spatial entity class geospatial data semantic-distance calculation heterogeneous database detailed definition matching process digital library relative importance
