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- W2386852905 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 suffcient 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." @default.
- W2386852905 created "2016-06-24" @default.
- W2386852905 creator A5091171038 @default.
- W2386852905 date "2010-01-01" @default.
- W2386852905 modified "2023-09-28" @default.
- W2386852905 title "A Query Interface Matching Approach Based on Extended Evidence Theory for Deep Web" @default.
- W2386852905 hasPublicationYear "2010" @default.
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