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M.J.: InstanceBased Matching of Large Ontologies Using Locality-Sensitive Hashing (2012)
| Venue: | In: Proceedings of the 11th International Semantic Web Conference, ISWC |
| Citations: | 6 - 2 self |
BibTeX
@INPROCEEDINGS{Duan12m.j.:instancebased,
author = {Songyun Duan and Achille Fokoue and Oktie Hassanzadeh and Anastasios Kementsietsidis and Kavitha Srinivas and Michael J. Ward},
title = {M.J.: InstanceBased Matching of Large Ontologies Using Locality-Sensitive Hashing},
booktitle = {In: Proceedings of the 11th International Semantic Web Conference, ISWC},
year = {2012}
}
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Abstract
Abstract. In this paper, we describe a mechanism for ontology align-ment using instance based matching of types (or classes). Instance-based matching is known to be a useful technique for matching ontologies that have different names and different structures. A key problem in instance matching of types, however, is scaling the matching algorithm to (a) handle types with a large number of instances, and (b) efficiently match a large number of type pairs. We propose the use of state-of-the art locality-sensitive hashing (LSH) techniques to vastly improve the scala-bility of instance matching across multiple types. We show the feasibility of our approach with DBpedia and Freebase, two different type systems with hundreds and thousands of types, respectively. We describe how these techniques can be used to estimate containment or equivalence re-lations between two type systems, and we compare two different LSH techniques for computing instance similarity.
