Establishing value mappings using statistical models and user feedback

Jaewoo Kang, Tae Sik Han, Dongwon Lee, Prasenjit Mitra

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

5 Citations (Scopus)

Abstract

In this paper, we present a "value mapping" algorithm that does not rely on syntactic similarity or semantic interpretation of the values. The algorithm first constructs a statistical model (e.g., co-occurrence frequency or entropy vector) that captures the unique characteristics of values and their co-occurrence. It then finds the matching values by computing the distances between the models while refining the models using user feedback through iterations. Our experimental results suggest that our approach successfully establishes value mappings even in the presence of opaque data values and thus can be a useful addition to the existing data integration techniques.

Original languageEnglish
Title of host publicationCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery (ACM)
Pages68-75
Number of pages8
ISBN (Print)1595931406, 9781595931405
DOIs
Publication statusPublished - 2005
EventCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany
Duration: 2005 Oct 312005 Nov 5

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

OtherCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
CountryGermany
CityBremen
Period05/10/3105/11/5

Keywords

  • Semantic Correspondences
  • Statistical Model
  • User Feedback
  • Value Mapping

ASJC Scopus subject areas

  • Business, Management and Accounting(all)

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  • Cite this

    Kang, J., Han, T. S., Lee, D., & Mitra, P. (2005). Establishing value mappings using statistical models and user feedback. In CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management (pp. 68-75). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery (ACM). https://doi.org/10.1145/1099554.1099569