Topic maps Matching and Merging Techniques based on Partitioning of Topics


The KIPS Transactions:PartD, Vol. 14, No. 7, pp. 819-828, Dec. 2007
10.3745/KIPSTD.2007.14.7.819,   PDF Download:

Abstract

In this paper, we propose a topic maps matching and merging approach based on the syntactic or semantic characteristics and constraints of the topic maps. Previous schema matching approaches have been developed to enhance effectiveness and generality of matching techniques. However they are inefficient because the approaches should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. Now, standard languages for developing ontologies are RDF/OWL and Topic Maps. In this paper, we propose an enhanced version of matching and merging technique based on topic partitioning, several matching operations and merging conflict detection.


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Cite this article
[IEEE Style]
J. M. Kim and H. S. Chung, "Topic maps Matching and Merging Techniques based on Partitioning of Topics," The KIPS Transactions:PartD, vol. 14, no. 7, pp. 819-828, 2007. DOI: 10.3745/KIPSTD.2007.14.7.819.

[ACM Style]
Jung Min Kim and Hyun Sook Chung. 2007. Topic maps Matching and Merging Techniques based on Partitioning of Topics. The KIPS Transactions:PartD, 14, 7, (2007), 819-828. DOI: 10.3745/KIPSTD.2007.14.7.819.