新しい自己組織化マップに基づくR-tree:構築と検索

Translated title of the contribution: A New SOM-based R*-tree: Building and Retrieving

Yaokai Feng, 久保 正明, Zaher Aghbari

Research output: Contribution to journalArticlepeer-review

Abstract

R-trees are widely used in spatial and multi-dimensional databases. However, according to our investigation, the overlap among the leaf nodes of R-trees is serious and the objects are not well-clustered in the leaf nodes, which greatly affect the effect of the pruning strategies when nearest neighbor searching is performed and also affect the other search performance of R-trees. The forced reinsertion introduced in R*-tree can improve this problem to some extent, but can not completely solve this problem. In this study, we try to combine SUM (Self Organizing Map) technology and R*-tree technology to lessen the overlap among the leaf nodes of R*-tree and to improve the clustering degree of the objects in the leaf nodes. The experimental result shows that the SUM-based R*-tree proposed in this paper has a much better search performance than R*-tree.
Translated title of the contributionA New SOM-based R*-tree: Building and Retrieving
Original languageJapanese
Pages (from-to)209-214
Number of pages6
JournalResearch Reports on Information Science and Electrical Engineering of Kyushu University
Volume6
Issue number2
DOIs
Publication statusPublished - Sep 2001

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