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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Cluster Analysis Using Rough Clustering and k-Means Clustering

Cluster Analysis Using Rough Clustering and k-Means Clustering
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Author(s): Kevin E. Voges (University of Canterbury, New Zealand)
Copyright: 2005
Pages: 4
Source title: Encyclopedia of Information Science and Technology, First Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-553-5.ch077


View Cluster Analysis Using Rough Clustering and k-Means Clustering on the publisher's website for pricing and purchasing information.


Cluster analysis is a fundamental data reduction technique used in the physical and social sciences. The technique is of interest to managers in information science because of its potential use in identifying user needs though segmenting users such as Web site visitors. In addition, the theory of rough sets is the subject of intense interest in computational intelligence research. The extension of this theory into rough clustering provides an important and potentially useful addition to the range of cluster analysis techniques available to the manager.

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