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SPARK2: Top-k Keyword Query in Relational Databases

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6 Author(s)
Yi Luo ; Lab. Le2i, CNRS Dijon, Dijon, France ; Wei Wang ; Xuemin Lin ; Xiaofang Zhou
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With the increasing amount of text data stored in relational databases, there is a demand for RDBMS to support keyword queries over text data. As a search result is often assembled from multiple relational tables, traditional IR-style ranking and query evaluation methods cannot be applied directly. In this paper, we study the effectiveness and the efficiency issues of answering top-k keyword query in relational database systems. We propose a new ranking formula by adapting existing IR techniques based on a natural notion of virtual document. We also propose several efficient query processing methods for the new ranking method. We have conducted extensive experiments on large-scale real databases using two popular RDBMSs. The experimental results demonstrate significant improvement to the alternative approaches in terms of retrieval effectiveness and efficiency.

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Knowledge and Data Engineering, IEEE Transactions on  (Volume:23 ,  Issue: 12 )