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Evaluating a confidence value for ontology alignment

by: Paulo Maio, Nuno Bettencourt, Nuno Silva, and João Rocha

In: Proceedings of the Workshop on Ontology Matching OM2007 at ISWC/ASWC2007, Busan, South Korea (November 2007) .

Abstract

Many methods for automatic and semi-automatic ontology alignment have been proposed, but they remain error prone and labor-intensive. This paper describes a novel generic process for evaluating the mappings' confidence value. This process uses rules extracted through inductive machine learning methods from the matching results proposed by others. Further, the precision and recall of the extracted rules are exploited in order to transform each rule into a mathematical formula that generates the mappings' confidence value. Mappings are then classified not as valid or invalid but through a quantitative confidence value that can be easily managed during the alignment process.

BibTeX record

@inproceedings{Maio/2007/Evaluating,
  abstract = {Many methods for automatic and semi-automatic ontology alignment have been proposed, but they remain error prone and labor-intensive. This paper describes a novel generic process for evaluating the mappings' confidence value. This process uses rules extracted through inductive machine learning methods from the matching results proposed by others. Further, the precision and recall of the extracted rules are exploited in order to transform each rule into a mathematical formula that generates the mappings' confidence value. Mappings are then classified not as valid or invalid but through a quantitative confidence value that can be easily managed during the alignment process.},
  added-at = {2007-11-07T19:19:06.000+0100},
  author = {Maio, Paulo and Bettencourt, Nuno and Silva, Nuno and Rocha, João},
  biburl = {http://www.bibsonomy.org/bibtex/2d0661d551bf47178899ef6a3fccad82d/iswc2007},
  booktitle = {Proceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Korea},
  crossref = {http://data.semanticweb.org/workshop/om/2007/proceedings},
  editor = {Shvaiko, Pavel and Euzenat, Jérôme and Giunchiglia, Fausto and He, Bin},
  interhash = {2e2393cb340a708c319c8ecfd4d8131e},
  intrahash = {d0661d551bf47178899ef6a3fccad82d},
  keywords = {2007 alignment confidence iswc ontology value workshop_om},
  month = {November},
  timestamp = {2007-11-07T19:19:06.000+0100},
  title = {Evaluating a confidence value for ontology alignment},
  year = 2007
}

Endnote record

%0 Conference Paper
%1 Maio/2007/Evaluating
%A Maio, Paulo
%A Bettencourt, Nuno
%A Silva, Nuno
%A Rocha, João
%B Proceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Korea
%D 2007
%E Shvaiko, Pavel
%E Euzenat, Jérôme
%E Giunchiglia, Fausto
%E He, Bin
%K 
%T Evaluating a confidence value for ontology alignment
%X Many methods for automatic and semi-automatic ontology alignment have been proposed, but they remain error prone and labor-intensive. This paper describes a novel generic process for evaluating the mappings' confidence value. This process uses rules extracted through inductive machine learning methods from the matching results proposed by others. Further, the precision and recall of the extracted rules are exploited in order to transform each rule into a mathematical formula that generates the mappings' confidence value. Mappings are then classified not as valid or invalid but through a quantitative confidence value that can be easily managed during the alignment process.