TY - GEN A1 - Weber, Marcus T1 - Clustering by using a simplex structure N2 - 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. T3 - ZIB-Report - 04-03 KW - cluster algorithms KW - Perron cluster analysis KW - stochastic matrices KW - bipartite graphs Y1 - 2003 UR - https://opus4.kobv.de/opus4-zib/frontdoor/index/index/docId/778 UR - https://nbn-resolving.org/urn:nbn:de:0297-zib-7782 ER -