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JCSE, vol. 8, no. 2, pp.94-106, June, 2014

DOI: http://dx.doi.org/10.5626/JCSE.2014.8.2.94

Appearance-Order-Based Schema Matching

Guohui Ding, Keyan Cao and Guoren Wang, Dong Han
Department of Computer Science, Shenyang Aerospace University, Shenyang, China / Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang, and College of Information Science & Engineering, Northeastern University, Shenyang, China / National Marine Data and Information Service, Tianjin, China

Abstract: Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.

Keyword: Schema matching; Data integration; Attributes; Correspondences; Appearance order; Similarity

Full Paper:   156 Downloads, 2021 View

 
 
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