778 eng reportzib 0 2003-12-19 2003-12-19 -- In this paper we interpret clustering as a mapping of data into a simplex. If the data itself has simplicial struture this mapping becomes linear. Spectral analysis is an often used tool for clustering data. We will show that corresponding singular vectors or eigenvectors comprise simplicial structure. Therefore they lead to a cluster algorithm, which consists of a simple linear mapping. An example for this kind of algorithms is the Perron cluster analysis (PCCA). We have applied it in practice to identify metastable sets of molecular dynamical systems. In contrast to other algorithms, this kind of approach provides an a priori criterion to determine the number of clusters. In this paper we extend the ideas to more general problems like clustering of bipartite graphs. 04-03 779 urn:nbn:de:0297-zib-7782 Marcus Weber 04-03 eng uncontrolled cluster algorithms eng uncontrolled Perron cluster analysis eng uncontrolled stochastic matrices eng uncontrolled bipartite graphs Informatik, Informationswissenschaft, allgemeine Werke Classification and discrimination; cluster analysis [See also 68T10] Eigenvalues, eigenvectors ZIB Allgemein Weber, Marcus https://opus4.kobv.de/opus4-zib/files/778/ZR-04-03.ps https://opus4.kobv.de/opus4-zib/files/778/ZR-04-03.pdf