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Abstract

On Partitioning for Ontology Alignment?Sunny Pereira1, Valerie Cross1, Ernesto Jiménez-Ruiz21Miami University, Oxford, OH 45056, United States2University of Oslo, Norway1 IntroductionOntology Alignment (OA) is the process of determining the mappings between twoontologies. A number of systems currently exists and many of them are participating inthe annual Ontology Alignment Evaluation Initiative (OAEI).3Ontology alignment for two very large ontologies becomes time consuming andmemory intensive. For example, thelargebiotrack in the OAEI campaign still posesserious challenges to participants and only 4 out of 11 systems managed to completethe largestlargebiotask. A general approach to address these challenges is to partitioneach ontology into cohesive blocks. The matching task is then divided into smaller tasksinvolving only relevant pair of blocks (i.e., partitions). Ontology partitioning brings newchallenges: how best to partition each ontology into blocks and whether the partitioningprocess on each ontology should be independent of each other. Three main strategiesexist:(i)totally independent partitioning of both ontologies using various clusteringalgorithms,(ii)independent partitioning of the better structured ontology and then useits partitioning to direct the partitioning of the other, and(iii)dependent partitioningbetween the two using a quick and efficient initial mapping of the two and then thismapping directs their partitioning.A preliminary study of these three partitioning strategies and their effects on ontol-ogy alignment is presented. The objective of this preliminary work is to determine thesuitability of these strategies to improve the performance of OA systems when dealingwith large ontologies, especially those unable to cope with the largest tasks.

Publication Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments:	School of Science & Technology > Computer Science School of Health & Psychological Sciences > Healthcare Services Research & Management > Food Policy

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