Clustering Spatial Data for Aggregate Query Processing in Walkthrough: A Hypergraph Approach

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.

[1]  Yuanchen Zhu,et al.  Uniform remeshing with an adaptive domain: a new scheme for view-dependent level-of-detail rendering of meshes , 2005, IEEE Transactions on Visualization and Computer Graphics.

[2]  Shao-Shin Hung,et al.  Using prefetching to improve walkthrough latency , 2006, Comput. Animat. Virtual Worlds.

[3]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[4]  Rynson W. H. Lau,et al.  CyberWalk: a web-based distributed virtual walkthrough environment , 2003, IEEE Trans. Multim..

[5]  Andrea C. Arpaci-Dusseau,et al.  Semantically-Smart Disk Systems , 2003, FAST.

[6]  Berkant Barla Cambazoglu,et al.  Clustering spatial networks for aggregate query processing: A hypergraph approach , 2008, Inf. Syst..

[7]  P. Jaccard.  THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1 , 1912 .

[8]  Meenakshisundaram Gopi,et al.  A novel page-based data structure for interactive walkthroughs , 2009, I3D '09.

[9]  Dinesh Manocha,et al.  Cache‐Efficient Layouts of Bounding Volume Hierarchies , 2006, Comput. Graph. Forum.

[10]  Vipin Kumar,et al.  Clustering Based On Association Rule Hypergraphs , 1997, DMKD.

[11]  Min Chen,et al.  Knowledge-Based Out-of-Core Algorithms for Data Management in Visualization , 2006, EuroVis.

[12]  Denis Lalanne,et al.  Investigating and reflecting on the integration of automatic data analysis and visualization in knowledge discovery , 2010, SKDD.

[13]  Andrew B. Kahng,et al.  A fast hierarchical quadratic placement algorithm , 2006, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[14]  Dimitri Plemenos,et al.  Visual Complexity and Intelligent Computer Graphics Techniques Enhancements , 2009, Studies in Computational Intelligence.