Clustering spatial data for aggregate query processing in walkthrough: A hypergraph approach

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Abstract

Nowadays, classical 3D object management systems use only direct visible properties and common features to model relationships between objects. In this paper we propose a new Object-oriented HyperGraph-based Clustering (OHGC) approach based on a behavioral walkthrough system that uses traversal patterns to model relationships between users and exploits semantic-based clustering techniques, such as association, intra-relationships, and inter-relationships, to explore additional links throughout the behavioral walkthrough system. The final aim consists in involving these new links in prediction generation, to improve performance of walkthrough system. OHGC is evaluated in terms of response time and number of retrieved objects on a real traversal dataset. © 2012 Springer-Verlag Berlin Heidelberg.

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Hung, S. S., Chiu, C. M., Fu, T. T., Chen, J. T., Tsaih, D., & Tsay, J. J. (2012). Clustering spatial data for aggregate query processing in walkthrough: A hypergraph approach. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7145 LNCS, 86–98. https://doi.org/10.1007/978-3-642-29050-3_8

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