NDLI: A top-down search grid based algorithm for fast subspace clustering

Content Provider	IEEE Xplore Digital Library
Author	Qiang Zhang Xi Chen Wei-Gong Chang Jie Zhang
Copyright Year	2008
Description	Author affiliation: Comput. Sci. & Inf. Eng. Coll., Tianjin Univ. of Sci. & Technol., Tianjin (Qiang Zhang; Xi Chen; Wei-Gong Chang)
Abstract	In this paper, a top-down search grid based algorithm is proposed to search all subspace that may contain clusters. Different from bottom-up search grid algorithms, the new approach starts from high-level subspace to low-level subspace, avoiding a lot of useless computation. Active spaces and grids are introduced to prune the search space, which reduces searching candidates dramatically. A new filter method based on active axis numbers is adopted to filter noise objects, since the noise is more serious in high-dimensional space. The advantages of the new approach are: it can discover clusters both on entire space and subspace; the computation complexity is proximate linear with objectpsilas number, space dimension, and clusterspsila dimension respectively; it is not sensitive to noise; it can find both disjoint clusters or overlap clusters; it can find clusters of arbitrary shape; it is also able to find any number of clusters in any number of dimensions and the number is not predetermined by a parameter.
Starting Page	180
Ending Page	183
File Size	173876
Page Count	4
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620400
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Noise Complexity theory Partitioning algorithms Data mining Presses Search problems active grid Subspace clustering High-dimensional top-down active space
Content Type	Text
Resource Type	Article

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