Abstract
Nowadays, data dissemination often involves online databases that are hidden behind query forms, thus forming the deep web. Lately, there has been a lot of research interest on supporting query answering over the deep web. To answer a deep web query efficiently, the current approaches generate a query plan for each query independently.
However, in practice, deep web queries issued by a user over a short period of time can often share similarities. This, if properly utilized, can help us in generating more efficient query plan. In this paper, we have developed a solution for generating query plan for a deep web query based on the similarities between a given query and a set of earlier queries. Our algorithm systematically finds the reusable components of earlier query plans, and then develops a new query plan reusing these. While the resulting query plans may not be optimal, they are likely to enable more data reuse, and hence, speedup the execution.
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Wang, F., Agrawal, G. (2010). Query Reuse Based Query Planning for Searches over the Deep Web. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15251-1_5
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DOI: https://doi.org/10.1007/978-3-642-15251-1_5
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