MDSM: microarray database schema matching using the Hungarian method

Chen, Yi-Ping Phoebe, Prompramote, Supawan and Maire, Frederic 2006, MDSM: microarray database schema matching using the Hungarian method, Information sciences, vol. 176, no. 19, pp. 2771-2790, doi: 10.1016/j.ins.2005.11.015.

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Title MDSM: microarray database schema matching using the Hungarian method
Author(s) Chen, Yi-Ping Phoebe
Prompramote, Supawan
Maire, Frederic
Journal name Information sciences
Volume number 176
Issue number 19
Start page 2771
End page 2790
Publisher Elsevier Inc.
Place of publication Philadelphia, Pa.
Publication date 2006-10-03
ISSN 0020-0255
Keyword(s) microarray database schema
Hungarian method
similarity function
schema matching
Summary Current microarray databases use different terminologies and structures and thereby limit the sharing of data and collating of results between laboratories. Consequently, an effective integrated microarray data model is required. One important process to develop such an integrated database is schema matching. In this paper, we propose an effective schema matching approach called MDSM, to syntactically and semantically map attributes of different microarray schemas. The contribution from this work will be used later to create microarray global schemas. Since microarray data is complex, we use microarray ontology to improve the measuring accuracy of the similarity between attributes. The similarity relations can be represented as weighted bipartite graphs. We determine the best schema matching by computing the optimal matching in a bipartite graph using the Hungarian optimisation method. Experimental results show that our schema matching approach is effective and flexible to use in different kinds of database models such as; database schema, XML schema, and web site map. Finally, a case study on an existing public microarray schema is carried out using the proposed method.
Language eng
DOI 10.1016/j.ins.2005.11.015
Field of Research 080610 Information Systems Organisation
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2005, Elsevier Inc
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