Abstract
The information on the deep web is much more abundant than the surface web, so it is important to make the best use of it. However, in the process of query, it is difficult to avoid the so-called failed queries that make no result. Instead of notifying the user that there is no result, it is more cooperative to modify the raw query to return non-empty result set. Inspired by the observations on the deep web, this paper presents a query relaxation solution. Firstly, it applies the technique of query probing to obtain data samples from the underlying deep web databases. Based on these data samples, the important degree of attributes are obtained by employing approximate functional dependence. Secondly, the databases matching the query better are chosen and divided into some groups in terms of their schemas. Then the groups are organized into a directed acyclic graph called database relationship graph (DRG) to implement query relaxation. Finally, it returns some results satisfying the query better. We have conducted experiments to demonstrate the feasibility and the efficiency of the solution.
This research is supported by the National Natural Science Foundation of China under Grant No. 60673139, 60573090.
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Ma, Y., Shen, D., Kou, Y., Liu, W. (2008). An Effective Query Relaxation Solution for the Deep Web. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds) Progress in WWW Research and Development. APWeb 2008. Lecture Notes in Computer Science, vol 4976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78849-2_65
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DOI: https://doi.org/10.1007/978-3-540-78849-2_65
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