Incremental Neighborhood Graphs Construction for Multidimensional Databases Indexing

Authors:
Hakim Hacid;Tetsuya Yoshida
Affiliations:
Lyon 2 University, ERIC Laboratory- 5, avenue Pierre Mendès-France, 69676 Bron cedex, France;Hokkaido University, Grad. School of Information Science and Technology, N-14 W-9, Sapporo 060-0814, Japan
Venue:
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Year:
2007

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Abstract

The point location (neighborhood search) is a significant problem in several fields like databases and data mining. Neighborhood graphs are interesting representations of this problem in a multidimensional space. However, several problems related to neighborhood graphs are under research and require detailed work to solve them. These problems are mainly related to their high construction costs and to their updating difficulties. In this article, we deal with the point location problem by considering neighborhood graphs optimization. We propose and compare two strategies able to quickly build and update these structures.