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Network analysis / Cluster analysis / Information bottleneck method / Algorithm / Statistics / Multivariate statistics / Hierarchical clustering


Finding Representative Set from Massive Data Feng Pan, Wei Wang University of North Carolina at Chapel Hill [removed] [removed]
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Document Date: 2005-11-21 15:44:08

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File Size: 237,35 KB

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City

Springer-Verlag / Wiley / /

Company

The 20 Newsgroup / Google / /

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Facility

Chapel Hill / Wei Wang University of North Carolina / Anthony K. H. Tung National University / /

IndustryTerm

simplified greedy algorithm / representative-based clustering algorithms / heuristic algorithm / word clustering algorithm / clustering algorithm / greedy algorithm / divisive information-theoretic feature clustering algorithm / manual processing / search criterion / web search / hierarchical clustering algorithm / cluster algorithms / search results / /

MarketIndex

Set 70 / SET 100 / set 20 / /

NaturalFeature

Chapel Hill / /

Organization

National Science Foundation / National University of Singapore / University of North Carolina / Case Western Reserve University / /

Person

E. Given / Max Coverage / Anthony K. H. Tung / Set / Max Cover / Coverage Represent / Maximum Coverage / /

Position

identifying representative / good representative / representative for each group / Representative / Finding representative / special representative / single representative / virtual representative / /

Product

L(r) / L / /

ProvinceOrState

New York / /

Technology

heuristic algorithm / hierarchical clustering algorithm / three algorithms / representative-based clustering algorithms / divisive information-theoretic feature clustering algorithm / set E. Our algorithm / two-phase clustering algorithm / 1 Greedy Algorithm / SUMMARY algorithm / greedy algorithm / simplified greedy algorithm / clustering algorithm / cluster algorithms / machine learning / especially representative-based clustering algorithms / word clustering algorithm / simplified algorithm / /

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