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Dwi H. Widyantoro
School of Electrical Engineering and Informatics, Institute of Technology Bandung Bandung, 40132 INDONESIA
Engineering

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Exploiting Homogeneity of Density in Incremental Hierarchical Clustering Dwi H. Widyantoro
Journal of Engineering and Technological Sciences Vol. 38 No. 2 (2006)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.eng.sci.2006.38.2.1

Abstract

Hierarchical clustering is an important tool in many applications. As it involves a large data set that proliferates over time, reclustering the data set periodically is not an efficient process. Therefore, the ability to incorporate a new data set incrementally into an existing hierarchy becomes increasingly demanding. This article describes HOMOGEN, a system that employs a new algorithm for generating a hierarchy of concepts and clusters incrementally from a stream of observations. The system aims to construct a hierarchy that satisfies the homogeneity and the monotonicity properties. Working in a bottom-up fashion, a new observation is placed in the hierarchy and a sequence of hierarchy restructuring processes is performed only in regions that have been affected by the presence of the new observation. Additionally, it combines multiple restructuring techniques that address different restructuring objectives to get a synergistic effect. The system has been tested on a variety of domains including structured and unstructured data sets. The experimental results reveal that the system is able to construct a concept hierarchy that is consistent regardless of the input data order and whose quality is comparable to the quality of those produced by non incremental clustering algorithms.
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