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Similarity Measurement in Context

Keßler Carsten

Research article in edited proceedings (conference) | Peer reviewed

Abstract

Context plays a crucial role when measuring the similarity of two concepts. Nonetheless, the modelling of context has been mostly neglected in existing similarity measurement theories. In this paper, we explore the influence of context in existing similarity measurement approaches for the geospatial domain, focussing on whether and how these approaches account for it. Based on these observations, the processing of context during similarity measurement is analysed, and general implementation issues, especially ease of integration into existing reasoning systems and computability, are discussed. The results of the different analyses are then combined into a generic set of characteristics of context for similarity measurement, with regard to the geospatial domain.

Details about the publication

Publisher: Kokinov, B., Richardson, D., Roth-Berghofer, Th., Vieu, L.
Book title: Modeling and Using Context. 6th International and Interdisciplinary Conference, CONTEXT 2007, Roskilde, Denmark, August 20-24, 2007, Proceedings
Page range: 277-290
Publishing company: Springer
Title of series: Lecture Notes in Artificial Intelligence
Volume of series: 4635
Status: Published
Release year: 2007
Language in which the publication is written: English
Conference: CONTEXT 2007, Copenhagen, Denmark, undefined
Link to the full text: http://ifgi.uni-muenster.de/~kessler/Carsten_Kessler_(2007)_Similarity_Measurement_in_Context.pdf

Authors from the University of Münster

Keßler, Carsten
Institute for Geoinformatics (ifgi)