Making sense of top-k matchings: A unified match graph for schema matching

Avigdor Gal, Tomer Sagi, Matthias Weidlich, Eliezer Levy, Victor Shafran, Zoltán Miklós, Nguyen Quoc Viet Hung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Schema matching in uncertain environments faces several challenges, among them the identification of complex correspondences. In this paper, we present a method to address this challenge based on top-k matchings, i.e., a set of matchings comprising only 1: 1 correspondences derived by common matchers. We propose the unified top-k match graph and define a clustering problem for it. The obtained attribute clusters are analysed to derive complex correspondences. Our experimental evaluation shows that our approach is able to identify a significant share of complex correspondences.

Original languageEnglish
Title of host publicationProceedings of the 9th International Workshop on Information Integration on the Web, IIWeb'12
DOIs
StatePublished - 2012
Externally publishedYes
Event9th International Workshop on Information Integration on the Web, IIWeb'12 - Scottsdale, AZ, United States
Duration: 20 May 201220 May 2012

Publication series

NameACM International Conference Proceeding Series

Conference

Conference9th International Workshop on Information Integration on the Web, IIWeb'12
Country/TerritoryUnited States
CityScottsdale, AZ
Period20/05/1220/05/12

Keywords

  • complex correspondences
  • graph modularity
  • schema matching
  • top-k matching

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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