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A Query Interface Matching Approach Based on Extended Evidence Theory for Deep Web

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Abstract

Matching query interfaces is a crucial step in data integration across multiple Web databases. Different types of information about query interface schemas have been used to match attributes between schemas. Relying on a single aspect of information is not sufficient and the matching results of individual matchers are often inaccurate and uncertain. The evidence theory is the state-of-the-art approach for combining multiple sources of uncertain information. However, traditional evidence theory has the limitations of treating individual matchers in different matching tasks equally for query interface matching, which reduces matching performance. This paper proposes a novel query interface matching approach based on extended evidence theory for Deep Web. Our approach firstly introduces the dynamic prediction procedure of different matchers' credibilities. Then, it extends traditional evidence theory with the credibilities and uses exponentially weighted evidence theory to combine the results of multiple matchers. Finally, it performs matching decision in terms of some heuristics to obtain the final matches. Our approach overcomes the shortage of traditional method and can adapt to different matching tasks. Experimental results demonstrate the feasibility and effectiveness of our proposed approach.

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Jinan, 250014, China

    Yong-Quan Dong (Member, CCF), Qing-Zhong Li (Senior Member, CCF), Yan-Hui Ding (Member, CCF) & Zhao-Hui Peng (Member, CCF)

  2. School of Computer Science and Technology, Xuzhou Normal University, Xuzhou, 221000, China

    Yong-Quan Dong (Member, CCF)

Authors
  1. Yong-Quan Dong
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  2. Qing-Zhong Li
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  3. Yan-Hui Ding
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  4. Zhao-Hui Peng
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Corresponding author

Correspondence to Qing-Zhong Li.

Additional information

Supported by the National Natural Science Foundation of China under Grant No. 90818001 and the Natural Science Foundation of Shandong Province of China under Grant No. Y2007G24.

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Dong, YQ., Li, QZ., Ding, YH. et al. A Query Interface Matching Approach Based on Extended Evidence Theory for Deep Web. J. Comput. Sci. Technol. 25, 537–547 (2010). https://doi.org/10.1007/s11390-010-9343-z

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  • DOI: https://doi.org/10.1007/s11390-010-9343-z

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