Markov network based ontology matching
Ontology matching is a vital step whenever there is a need to integrate and reason about overlapping domains of knowledge. Systems that automate this task are of a great need. iMatch is a probabilistic scheme for ontology matching based on Markov networks, which has several advantages over other pro...
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| Veröffentlicht in: | Journal of computer and system sciences 2012, Vol.78 (1), p.105-118 |
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| container_title | Journal of computer and system sciences |
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| creator | Albagli, Sivan Ben-Eliyahu-Zohary, Rachel Shimony, Solomon E. |
| description | Ontology matching is a vital step whenever there is a need to integrate and reason about overlapping domains of knowledge. Systems that automate this task are of a great need. iMatch is a probabilistic scheme for ontology matching based on Markov networks, which has several advantages over other probabilistic schemes. First, it handles the high computational complexity by doing approximate reasoning, rather then by ad-hoc pruning. Second, the probabilities that it uses are learned from matched data. Finally, iMatch naturally supports interactive semi-automatic matches. Experiments using the standard benchmark tests that compare our approach with the most promising existing systems show that iMatch is one of the top performers. |
| doi_str_mv | 10.1016/j.jcss.2011.02.014 |
| format | Article |
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| ispartof | Journal of computer and system sciences, 2012, Vol.78 (1), p.105-118 |
| issn | 0022-0000 1090-2724 |
| language | eng |
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| source | Elsevier ScienceDirect Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Approximation Interactive Markov networks Markov processes Matching Networks Ontology matching Probabilistic methods Probabilistic reasoning Probability theory Tasks |
| title | Markov network based ontology matching |
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