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Measuring Geospatial Semantic Similarity between Geospatial Entity Classes

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3 Author(s)
K. K. Win ; University of Computer Studies, Yangon, Myanmar. kkhaingwin@gmail.com ; K. Haymar ; Saw Hla

We have witnessed an increasing interest in GIScience and semantic Web technology. In the fast growing information age, available methods for finding and using information on the Web are often insufficient. Today's retrieval methods are typically limited to keywords searches or sub string matches; therefore, users may often miss critical information when searching the Web. A query system is needed to support efficient geospatial information retrieval based on geospatial relations. We need to combine GIScience and semantic Web technology. To accomplish the development of geospatial semantic Web, two research issues are apparent: 1st is geospatial data query and 2nd is method to assess the semantics of available data sources. We have proposed to develop geospatial semantic query system by integrating geospatial reasoning. In this paper, we propose a method to extend and enhance semantic similarity measures between geospatial entity classes. We need to measure semantic similarity and geospatial similarity to query geospatial semantic. So, our proposed method contains two portions. The first portion contains a function of semantic similarity to measure semantic similarity of geospatial entity classes. The second portion contains a function of geospatial similarity (GSS) to measure spatial similarity of geospatial entity classes that have semantic similarity. This similarity function determines spatially similar results by using the fundamental logical or Boolean operators

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2006 2nd International Conference on Information & Communication Technologies  (Volume:1 )

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