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- 229 creator gwenn-englebienne.
- 229 creator shenghui-wang.
- 229 creator stefan-schlobach.
- 229 type InProceedings.
- 229 label "Learning Concept Mappings from Instance Similarity".
- 229 sameAs 229.
- 229 abstract "Finding mappings between compatible ontologies is an important but difficult open problem. Instance-based methods for solving this problem have the advantage of focusing on the most active parts of the ontologies and reflect concept semantics as they are used in the real world. However such methods have not at present been widely investigated in ontology mapping, compared to linguistic and structural techniques. In this paper we approach the mapping problem as a classification problem based on the similarity between instances of concepts. We evaluate the resulting classifier on three different real-world data sets.".
- 229 hasAuthorList authorList.
- 229 hasTopic Semantic_Web.
- 229 isPartOf proceedings.
- 229 keyword "Classification".
- 229 keyword "Machine learning".
- 229 keyword "Ontology".
- 229 keyword "Similarity".
- 229 keyword "Thesaurus mapping".
- 229 title "Learning Concept Mappings from Instance Similarity".