NDLI: Clustering by principal curve with tree structure

Content Provider	IEEE Xplore Digital Library
Author	Cleju, I. Franti, P. Xiaolin Wu
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. & Inf. Sci., Konstanz Univ., Germany (Cleju, I.)
Abstract	Data clustering is intensively used in signal processing in tasks such as multimedia compression, segmentation and pattern matching. In this work we extend the use of principal curves in clustering to complex multidimensional datasets. The use of principal curve in clustering is limited for high complexity data. Automatic parameterization of the principal curve to assure good results for different datasets is a difficult task. We propose to use the tree structure to capture the general settlement of the data. Using this topology, regions of the dataset can be extracted, individually clustered using the principal curve and then optimally recombined. The experiments show the improvement of the new method over the principal curve based clustering and the good performance compared to other clustering methods.
Starting Page	617
Ending Page	620
File Size	730356
Page Count	4
File Format	PDF
ISBN	0780390296
DOI	10.1109/ISSCS.2005.1511316
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-14
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tree data structures Computer science Information science Clustering algorithms Multimedia computing Quantization Partitioning algorithms Data mining Application software Pattern matching
Content Type	Text
Resource Type	Article

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