Parallel linkage

Hung Sik Kim, Dongwon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

34 Scopus citations


We study the parallelization of the (record) linkage problem - i.e., to identify matching records between two collections of records, A and B. One of main idiosyncrasies of the linkage problem, compared to Database join, is the fact that once two records a in A and b in B are matched and merged to c, c needs to be compared to the rest of records in A and B again since it may incur new matching. This re-feeding stage of the linkage problem requires its solution to be iterative, and complicates the problem significantly. Toward this problem, we first discuss three plausible scenarios of inputs - when both collections are clean, only one is clean, and both are dirty. Then, we show that the intricate interplay between match and merge can exploit the characteristics of each scenario to achieve good parallelization. Our parallel algorithms achieve 6.55-7.49 times faster in speedup compared to sequential ones with 8 processors, and 11.15-18.56% improvement in efficiency compared to P-Swoosh.

Original languageEnglish (US)
Title of host publicationCIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management
Number of pages10
StatePublished - Dec 1 2007
Event16th ACM Conference on Information and Knowledge Management, CIKM 2007 - Lisboa, Portugal
Duration: Nov 6 2007Nov 9 2007

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Other16th ACM Conference on Information and Knowledge Management, CIKM 2007

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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