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Data mining / Geostatistics / Machine learning / Fuzzy clustering / Statistics / Cluster analysis / Data analysis


Tracking Entities in the Dynamic World: A Fast Algorithm for Matching Temporal Records Yueh-Hsuan Chiang 1 , AnHai Doan 2 , Jeffrey F. Naughton 3 University of Wisconsin Madison[removed]W Dayton Street, Madison, WI 53706,
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Document Date: 2014-01-06 10:12:54


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Hangzhou / /

Company

Creative Commons / D IS AG / Intel / /

Country

China / /

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Event

Product Issues / Product Recall / /

Facility

University Zheng Y. / University of Wisconsin Madison / Wang Wei Zhejiang University / Wang Wei Fudan University / University Wei G. / /

IndustryTerm

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OperatingSystem

Linux / /

Organization

Concordia University / Purdue University / Wang Wei Univ / VLDB Endowment / Wei Univ / Fudan University / Zhejiang University / University of Wisconsin Madison / /

Person

Wang Wei Zhejiang / Wei Univ / Ai / Wang Wei / Wang Wei Concordia Univ Swamy / B. Liu / Ahmad M.O. Swamy / Wang Yuke / Jeffrey F. Naughton / /

Position

researcher / co-author / author / King / associated author / /

Product

minR / /

ProgrammingLanguage

Java / FP / /

ProvinceOrState

South Dakota / South Carolina / /

Technology

pass clustering algorithm / RAM / 475 Algorithm / two temporal clustering algorithms / Linux / two-phase clustering algorithm / temporal matching algorithm / clustering algorithm / adjusted binding algorithm / temporal clustering algorithm / three temporal record matching algorithms / existing record matching algorithms / temporal clustering algorithms / non-temporal clustering algorithm / existing non-temporal algorithms / 472 Algorithm / stateof-the-art temporal clustering algorithm / Java / partitioning algorithm / fuzzy clustering algorithm / hard clustering algorithm / state-of-theart temporal clustering algorithm / /

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