Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices
Mirkin, Boris and Nascimento, S. (2012) Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices. Information Sciences 183 (1), pp. 16-34. ISSN 0020-0255.
An additive spectral method for fuzzy clustering is proposed. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which makes the spectral approach quite natural. The iterative extraction of clusters, also, allows us to draw several stopping rules to the procedure. This applies to several relational data types differently normalized: network structure data (the first eigenvector subtracted), affinity between multidimensional vectors (the pseudo-inverse Laplacian transformation), and conventional relational data including in-house data of similarity between research topics according to working of a research center. The method is experimentally compared with several classic and recent techniques and shown to be competitive.
|Keyword(s) / Subject(s):||spectral fuzzy clustering, additive fuzzy clustering, one-by-one clustering, Lapin transformation, community structure, research activity structure|
|School:||Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems|
|Research Centre:||Structural Molecular Biology, Institute of (ISMB)|
|Date Deposited:||22 Sep 2011 08:01|
|Last Modified:||06 Dec 2016 10:33|
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