Abstract
The existing approaches of keyword search over relational databases usually first generate all possible results composed of relevant tuples and then sort them based on their individual ranks. These traditional methods are inefficient to identify the top-k answers with the highest ranks. This paper studies the problem of progressively identifying the top-k answers from the relational databases. The approach of progressively identifying the answers is very desirable as it generates the higher ranked results earlier thereby reducing the delay in responding to the user query. We have implemented our proposed method, and the experimental results show that our method outperforms existing state-of-the-art approaches and achieves much better search performance.
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Li, G., Feng, J., Lin, F., Zhou, L. (2008). Progressive Ranking for Efficient Keyword Search over Relational Databases. In: Gray, A., Jeffery, K., Shao, J. (eds) Sharing Data, Information and Knowledge. BNCOD 2008. Lecture Notes in Computer Science, vol 5071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70504-8_20
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DOI: https://doi.org/10.1007/978-3-540-70504-8_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70503-1
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