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dc.contributor.authorSingh, Gurjeeten_US
dc.contributor.authorMemoli, Facundoen_US
dc.contributor.authorCarlsson, Gunnaren_US
dc.contributor.editorM. Botsch and R. Pajarola and B. Chen and M. Zwickeren_US
dc.date.accessioned2014-01-29T16:52:11Z
dc.date.available2014-01-29T16:52:11Z
dc.date.issued2007en_US
dc.identifier.isbn978-3-905673-51-7en_US
dc.identifier.issn1811-7813en_US
dc.identifier.urihttp://dx.doi.org/10.2312/SPBG/SPBG07/091-100en_US
dc.description.abstractWe present a computational method for extracting simple descriptions of high dimensional data sets in the form of simplicial complexes. Our method, called Mapper, is based on the idea of partial clustering of the data guided by a set of functions defined on the data. The proposed method is not dependent on any particular clustering algorithm, i.e. any clustering algorithm may be used with Mapper. We implement this method and present a few sample applications in which simple descriptions of the data present important information about its structure.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling.en_US
dc.titleTopological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognitionen_US
dc.description.seriesinformationEurographics Symposium on Point-Based Graphicsen_US


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