Multivalued type proximity measure and concept of mutual ismilarity value useful for clustering symbolic patterns

Guru, D. S. and Kiranagi, B. B. and Nagabhushan, P. (2004) Multivalued type proximity measure and concept of mutual ismilarity value useful for clustering symbolic patterns. Pattern Recognition Letters, 25 (10). pp. 1203-1213. ISSN 0167-8655

[img] Text (Full Text)
Cmp_2004_Guru_Bapu_Nagabhusan.pdf - Published Version
Restricted to Registered users only

Download (299kB) | Request a copy
Official URL: doi:10.1016/j.patrec.2004.03.016

Abstract

In this paper, a novel similarity measure for estimating the degree of similarity between two patterns (described by interval type data) is proposed. The proposed measure computes the degree of similarity between two patterns and approximates the computed similarity value by a multivalued type data. Unlike conventional proximity matrices, the proximity matrix obtained through the application of the proposed similarity measure is not necessarily symmetric. Based on this unconventional similarity matrix a modified agglomerative method by introducing the concept of mutual similarity value (MSV) for clustering symbolic patterns is also presented. Experiments on various data sets have been conducted in order to study the efficacy of the proposed methodology. (C) 2004 Elsevier B.V. All rights reserved.

Item Type: Article
Uncontrolled Keywords: symbolic data analysis; proximity measures; interval valued data type; multivalued data type; mutual similarity value; clustering of data
Subjects: D Physical Science > Computer Science
Depositing User: Users 23 not found.
Date Deposited: 31 Aug 2019 09:10
Last Modified: 31 Aug 2019 09:10
URI: http://eprints.uni-mysore.ac.in/id/eprint/6566

Actions (login required)

View Item View Item