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An Ontology-Based Spatial Clustering Selection System

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Advances in Artificial Intelligence (Canadian AI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5549))

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Abstract

Spatial clustering, which groups similar spatial objects into classes, is an important research topic in spatial data mining. Many spatial clustering methods have been developed recently. However, many users do not know how to choose the most suitable spatial clustering method to implement their own projects due to lack of expertise in the area. In order to reduce the difficulties of choosing, linking and executing appropriate programs, we build a spatial clustering ontology to formalize a set of concepts and relationships in the spatial clustering domain. Based on the spatial clustering ontology, we implement an ontology-based spatial clustering selection system (OSCS) to guide users selecting an appropriate spatial clustering algorithm. The system consists of the following parts: a spatial clustering ontology, an ontology reasoner using a task-model, a web server and a user interface. Preliminary experiments have been conducted to demonstrate the efficiency and practicality of the system.

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Ā© 2009 Springer-Verlag Berlin Heidelberg

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Gu, W., Wang, X., ZiƩbelin, D. (2009). An Ontology-Based Spatial Clustering Selection System. In: Gao, Y., Japkowicz, N. (eds) Advances in Artificial Intelligence. Canadian AI 2009. Lecture Notes in Computer Science(), vol 5549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01818-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-01818-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01817-6

  • Online ISBN: 978-3-642-01818-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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