Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/eswc2009/paper/101> ?p ?o. }
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- 101 creator christian-meilicke.
- 101 creator heiner-stuckenschmidt.
- 101 creator kai-eckert.
- 101 type InProceedings.
- 101 label "Improving Ontology Matching using Meta-level Learning".
- 101 sameAs 101.
- 101 abstract "Despite serious research efforts, automatic ontology matching still suffers from severe problems with respect to the quality of matching results. Existing matching systems trade-off precision and recall and have their specific strengths and weaknesses. This leads to problems when the right matcher for a given task has to be selected. In this paper, we present a method for improving matching results by not choosing a specific matcher but applying machine learning techniques on an ensemble of matchers. Hereby we learn rules for the correctness of a correspondence based on the output of different matchers and additional information about the nature of the elements to be matched, thus leveraging the weaknesses of an individual matcher. We show that our method always performs significantly better than the median of the matchers used and in most cases outperforms the best matcher with an optimal threshold for a given pair of ontologies. As a side product of our experiments, we discovered that the majority vote is a simple but powerful heuristic for combining matchers that almost reaches the quality of our learning results.".
- 101 hasAuthorList authorList.
- 101 hasTopic Ontology_%28computer_science%29.
- 101 hasTopic Ontology_alignment.
- 101 hasTopic Semantic_Web.
- 101 isPartOf proceedings.
- 101 keyword "Evaluation".
- 101 keyword "Machine Learning".
- 101 keyword "Ontology Matching".
- 101 title "Improving Ontology Matching using Meta-level Learning".