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Cluster validity index for adaptive clustering algorithms

Content Provider	IET Digital Library
Author	Cui, Hongyan Xie, Mingzhi Cai, Yunlong Huang, Xu Liu, Yunjie
Abstract	Everyday a large number of records of surfing internet are generated. In various situations when the authors are analysing internet data they do not know the cluster structure of the author's database of traffic features, such as when the border of cluster members is vague, and the clusters’ partitions have different shapes, how to establish an algorithm to solve the clustering problem? Adaptive clustering algorithms can meet this challenge. Moreover, how to determinate the number of clusters when not only fuzzy cluster but also hard cluster are used? To address those problems, a new cluster validity index is proposed in this study. The proposed index focuses on the information of the geometrical structure of dataset by analysing the neighbourhood of data objects, which makes the index independent of the traditional fuzzy membership matrix. The new index consists of two parts, namely the ‘compactness’ and ‘separation measure’. The compactness indicates the degree of the similarity among the data objects in the same cluster. The separation measure indicates the degree of dissimilarity among the data objects in different clusters. The performance of their proposed index is excellent underpinned by the outcomes from the experiments based on both artificial datasets and real world datasets.
Starting Page	2256
Ending Page	2263
Page Count	8
ISSN	17518628
Volume Number	8
e-ISSN	17518636
Issue Number	Issue 13, Sep (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/8/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2013.0899
Journal	IET Communications
Publisher Date	2014-08-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Clustering Algorithm Artificial Datasets Author Database Cluster Members Cluster Partitions Cluster Structure Cluster Validity Index Data Analysis Data Handling Technique Data Objects Dataset Geometrical Structure Fuzzy Membership Matrix Hard Cluster Index Compactness Index Separation Measure Internet Internet Data Analysis Pattern Clustering Real World Datasets Traffic Feature
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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