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Clustering Pair-wise Dissimilarity Data into Partially Ordered Sets Jinze Liu, Qi Zhang, Wei Wang, Leonard McMillan, Jan Prins Department of Computer Science University of North Carolina, Chapel Hill, NC 27599 {liuj, zha
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Document Date: 2006-06-17 13:24:20

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Springer-Verlag / New YOrk / Ashburner / Philadelphia / Pittsburgh / Eppig / /

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Prentice-Hall / BP / DSWO Press / ABC / John Wiley and Sons Inc. / Plenum Press / Finding / P. Rousseeuw / Computerh-Based Medical Systems / Similarity Resnik LC / Accrue Software / Other Lexical Resources / L. Kaufman / /

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United States / /

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pence / USD / /

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Chapel Hill / Computer Science University of North Carolina / /

IndustryTerm

conventional hierarchical and pyramidal clustering algorithms / classical clustering algorithms / semantic web / approximation algorithm / disjoint clustering algorithms / Web Conference / data mining techniques https /

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U.S. Securities and Exchange Commission / R.J.cho and G. Church / University of North Carolina / Chapel Hill / North American Chapter / Association for Computational Linguistics / /

Person

G. Li / V / M.Q.Zhang / V / S. Tavazoie / R. O. Duda / M. Karp Reducibility / Gene Ontology / Wei Wang / J. L. Sevilla / V / Leonard McMillan / Jan Prins / /

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Data Mining General / H. Butler / JM / ordinal model for clustering / /

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M.B. / New York / Pennsylvania / California / Massachusetts / /

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Computational Linguistics / Nature Genetics / Molecular Biology / /

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three algorithms / Bioinformatics / Applying Algorithm / clustering algorithms / clustering algorithm / poCluster algorithm / approximation algorithm / disjoint clustering algorithms / DNA Chip / gene expression / three clustering algorithms / Data Mining / Classic clustering algorithms / incremental algorithm / classical clustering algorithms / conventional hierarchical and pyramidal clustering algorithms / /

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