NDLI: Fast Implementation of Dual Clustering Algorithm for Spatial Data Mining

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Volume 2 - 2007

Volume 1 - 2007

Fast Implementation of Dual Clustering Algorithm for Spatial Data Mining

Content Provider	IEEE Xplore Digital Library
Author	Jiaogen Zhou Fuling Bian Jihong Guan Meng Zhang
Copyright Year	2007
Description	Author affiliation: Wuhan Univ., Wuhan (Jiaogen Zhou; Fuling Bian)
Abstract	Many applications scenarios require spatial clustering results in which a cluster has not only high proximity in geometrical domain but also high similarity in non-geometrical domain. Such clustering problem is called dual clustering. We proposed a new algorithm for solving such problem. We first implemented density-based sampling on spatial dataset to reduce data size, and then we partitioned the sample to different clusters in such a way that each cluster forms a compact region in geometrical domain while has the similarity in non-geometrical domain. The experimental results show our algorithm is very effective and efficient.
Starting Page	568
Ending Page	572
File Size	302858
Page Count	5
File Format	PDF
ISBN	9780769528748
DOI	10.1109/FSKD.2007.288
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Clustering algorithms Scattering Sampling methods Data engineering Spatial databases Partitioning algorithms Data mining Application software Fuzzy systems
Content Type	Text
Resource Type	Article

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