Optimal learning of ontology mappings from human interactions
DSpace at IIT Bombay
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Title |
Optimal learning of ontology mappings from human interactions
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Creator |
SEN, S
FERNANDES, D SARDA, NL |
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Description |
Lexical similarity based ontology mappings are useful to obtain semantic translations of database schemas across application domains. Incremental improvement of such mappings can be obtained from human inputs of ontology mapping. Manual mappings are labor intensive and need to be assisted by machine-generated mappings in a semi-automated approach. Heuristics based approaches allow multiple strategies to learn human expertise in concept mappings. Such learning improves the level of automation of the mapping process. We analyze heuristics based Bayesian learning of manual mappings to improve effectiveness of machine-generated mappings. Our results show that human based mappings contribute higher improvement in the machine-generated values of lexical similarity in comparison to those of structural similarity. The optimal weightage for structural similarity learning is inversely proportional to the complexity of given ontology graphs.
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Publisher |
SPRINGER-VERLAG BERLIN
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Date |
2011-10-24T05:16:50Z
2011-12-15T09:11:30Z 2011-10-24T05:16:50Z 2011-12-15T09:11:30Z 2007 |
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Type |
Proceedings Paper
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Identifier |
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS 2007: COOPLS, DOA, ODBASE, GADA, AND IS, PT 1, PROCEEDINGS,49803,1025-1033
978-3-540-76846-3 0302-9743 http://dspace.library.iitb.ac.in/xmlui/handle/10054/15336 http://hdl.handle.net/100/2102 |
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Source |
OTM Confederated International Conference and Workshop,Vilamoura, PORTUGAL,NOV 25-30, 2007
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Language |
English
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