From diversity-based prediction to better ontology & schema matching

Avigdor Gal, Haggai Roitman, Tomer Sagi

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

22 Citations (Scopus)

Abstract

Ontology & schema matching predictors assess the quality of matchers in the absence of an exact match. We propose MCD (Match Competitor Deviation), a new diversity-based predictor that compares the strength of a matcher confidence in the correspondence of a concept pair with respect to other correspondences that involve either concept. We also propose to use MCD as a regulator to optimally control a balance between Precision and Recall and use it towards 1 : 1 matching by combining it with a similarity measure that is based on solving a maximum weight bipartite graph matching (MWBM). Optimizing the combined measure is known to be an NP-Hard problem. Therefore, we propose CEM, an approximation to an optimal match by efficiently scanning multiple possible matches, using rare event estimation. Using a thorough empirical study over several benchmark real-world datasets, we show that MCD outperforms other state-of-The-Art predictor and that CEM significantly outperform existing matchers.

Original languageEnglish
Title of host publication25th International World Wide Web Conference, WWW 2016
Number of pages11
PublisherInternational World Wide Web Conferences Steering Committee
Publication date2016
Pages1145-1155
ISBN (Electronic)9781450341431
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event25th International World Wide Web Conference, WWW 2016 - Montreal, Canada
Duration: 11 Apr 201615 Apr 2016

Conference

Conference25th International World Wide Web Conference, WWW 2016
Country/TerritoryCanada
CityMontreal
Period11/04/201615/04/2016
Sponsoret al., Google, Microsoft, Palais des Congres de Montreal, Tourisme Montreal, Yahoo
Series25th International World Wide Web Conference, WWW 2016

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