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Semantic-distance based evaluation of ranking queries over relational databases

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Abstract

Traditional database search uses pattern match in the comparison process. For a query with some search words, tuples are selected only if the words of the tuples exactly match the query words. In this paper, we propose a new method for evaluating relational ranking queries (or top-N queries) with text attributes. This method defines semantic distance functions and utilizes semantic match between words in database search. The attempt is that tuples, not only exactly matching, but also close to the query according to semantic distances, can both be fetched. The basic idea of the method is to create an index based on WordNet to expand the tuple words semantically. The candidate results for a query are retrieved by the index and a simple SQL selection statement, and then top-N answers are obtained. Extensive experiments are carried out to measure the performance of this new strategy for the evaluation of ranking queries over relational databases.

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Notes

  1. A relationship L on the sets X 1, ..., X k is a subset of their Cartesian product, written \(L \subseteq X_{1} \times \) ... ×X k .

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Acknowledgements

This work is supported in part by the NSFC(30971693, 60873145), Hebei University PhD grant (2009-160), and the key project of applied fundamental research and the NSF of Hebei Province (08963522D, F2008000635). The authors would also like to express their gratitude to Professor Weiyi Meng for providing many helpful suggestions, and to Shenda Ji and Yanchao Feng who helped to recognize the semantic match between queries and answers.

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Authors and Affiliations

  1. Key Laboratory of Machine Learning and Computational Intelligence, School of Mathematics and Computer Science, Hebei University, Baoding, Hebei, 071002, China

    Liang Zhu & Wenzhu Yang

  2. Department of Foreign Language Teaching and Research, Hebei University, Baoding, Hebei, 071002, China

    Qin Ma

  3. College of Computer Science and Technology, Beijing University of Technology, Beijing, 100124, China

    Chunnian Liu & Guojun Mao

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  1. Liang Zhu
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  2. Qin Ma
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  3. Chunnian Liu
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  4. Guojun Mao
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  5. Wenzhu Yang
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Correspondence to Qin Ma.

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Zhu, L., Ma, Q., Liu, C. et al. Semantic-distance based evaluation of ranking queries over relational databases. J Intell Inf Syst 35, 415–445 (2010). https://doi.org/10.1007/s10844-009-0116-5

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  • DOI: https://doi.org/10.1007/s10844-009-0116-5

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