Summary
Against the background that one-mode clustering, which is based on similarity or dissimilarity data, is well known and widely used, quite a number of generalizations of the basic clustering methodology have been developed. For so-called two-mode data we report on research within the area of two-mode clustering and describe the new AE (Alternating Exchanges) algorithm. For non- overlapping two-mode clustering this algorithm is based on the exchange of the cluster membership of elements from the sets of different modes. Therefore, it is simple and very fast. The results of applying this algorithm to several concrete data sets are compared to those of an own PENCLUS (PENalty CLUStering) approach.
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© 1996 Springer-Verlag Berlin · Heidelberg
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Gaul, W., Schader, M. (1996). A New Algorithm for Two-Mode Clustering. In: Bock, HH., Polasek, W. (eds) Data Analysis and Information Systems. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80098-6_2
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DOI: https://doi.org/10.1007/978-3-642-80098-6_2
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