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Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics

Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics

Nicola Fanizzi, Claudia d’Amato, Floriana Esposito
Copyright: © 2008 |Volume: 4 |Issue: 3 |Pages: 24
ISSN: 1552-6283|EISSN: 1552-6291|ISSN: 1552-6283|EISBN13: 9781615204847|EISSN: 1552-6291|DOI: 10.4018/jswis.2008070103
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MLA

Fanizzi, Nicola, et al. "Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics." IJSWIS vol.4, no.3 2008: pp.44-67. http://doi.org/10.4018/jswis.2008070103

APA

Fanizzi, N., d’Amato, C., & Esposito, F. (2008). Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics. International Journal on Semantic Web and Information Systems (IJSWIS), 4(3), 44-67. http://doi.org/10.4018/jswis.2008070103

Chicago

Fanizzi, Nicola, Claudia d’Amato, and Floriana Esposito. "Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics," International Journal on Semantic Web and Information Systems (IJSWIS) 4, no.3: 44-67. http://doi.org/10.4018/jswis.2008070103

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Abstract

We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a semi-distance measure defined for individuals, that is based on a finite number of dimensions corresponding to a committee of discriminating features (concept descriptions). A maximally discriminating group of features is obtained with a randomized optimization method. In the algorithm, the possible clusterings are represented as medoids (w.r.t. the given metric) of variable length. The number of clusters is not required as a parameter, the method is able to find an optimal choice by means of evolutionary operators and a proper fitness function. An experimentation proves the feasibility of our method and its effectiveness in terms of clustering validity indices. With a supervised learning phase, each cluster can be assigned with a refined or newly constructed intensional definition expressed in the adopted language.

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