An architecture for component-based design of representative-based clustering algorithms

Authors:
Boris Delibašić;Milan Vukićević;Miloš Jovanović;Kathrin Kirchner;Johannes Ruhland;Milija Suknović
Affiliations:
Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, Belgrade, Serbia;Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, Belgrade, Serbia;Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, Belgrade, Serbia;Faculty of Economics and Business Administration, Friedrich Schiller University of Jena, Carl-Zeií Straíe 3, Jena, Germany;Faculty of Economics and Business Administration, Friedrich Schiller University of Jena, Carl-Zeií Straíe 3, Jena, Germany;Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, Belgrade, Serbia
Venue:
Data & Knowledge Engineering
Year:
2012

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Abstract

We propose an architecture for the design of representative-based clustering algorithms based on reusable components. These components were derived from K-means-like algorithms and their extensions. With the suggested clustering design architecture, it is possible to reconstruct popular algorithms, but also to build new algorithms by exchanging components from original algorithms and their improvements. In this way, the design of a myriad of representative-based clustering algorithms and their fair comparison and evaluation are possible. In addition to the architecture, we show the usefulness of the proposed approach by providing experimental evaluation.