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Ranking Algorithms for Keyword Search over Relational Databases

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Abstract:

Developing effective ranking algorithms for keyword search over relational databases is a hot study topic. Ranking algorithm largely determines the performance of a keyword search system. Good ranking algorithms not only provide user with the most relevant query results but also provide fast response time. A number of existing ranking algorithms were classified and compared. Several representational algorithms were summarized and analysed in detail. The principles, advantages and disadvantages of these algorithms were discussed. Finally, prospect for future work, especially the intelligent trends, in ranking were discussed.

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Periodical:

Advanced Materials Research (Volumes 605-607)

Pages:

2291-2296

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.605-607.2291

Citation:

Cite this paper

Online since:

December 2012

Authors:

Chao Wang, Jie Ding, Bin Hu

Keywords:

Keyword Search, Ranking Algorithm, Relational Databases, Relevance Score

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] V. Hristidis and Y. Papakonstantinou, in: VLDB, (2002).

Google Scholar

[2] G. Bhalotia, C. Nakhey, A. Hulgeri, S. Chakrabarti and S. Sudarshan, in: ICDE, (2002).

Google Scholar

[3] V. Hristidis, H. Hwang and Y. Papakonstantinou: ACM Trans. Database Syst. Vol.33 (2008).

Google Scholar

[4] H. He, H. X. Wang, J. Yang and P. S. Yu, in: ACM SIGMOD, (2007).

Google Scholar

[5] Z. Zeng, Z. F. Bao, T. W. Ling and M. L. Lee, in: Proceedings of the Third International Workshop on Keyword Search on Structured Data, (2012).

Google Scholar

[6] S. Agrawal, S. Chaudhuri, and G. Das, in: ICDE, (2002).

Google Scholar

[7] V. Hristidis, L. Gravano and Y. Papakonstantinou, in: VLDB, (2003).

Google Scholar

[8] J. J. Wen and S. Wang: Journal of Software, Vol. 16, (2005), p.1270.

Google Scholar

[9] Y. Luo, X. Lin, W. Wang and X. Zhou, in: ACM SIGMOD, (2007).

Google Scholar

[10] Y. W. Xu, Y. Ishikawa and J. H. Guan, in: DBIR-ENQOIR, (2009), p.172.

Google Scholar

[11] G. L Li, S.Y. Ji, C. Li and J. H. Feng, in: SIGMOD, (2009), p.695.

Google Scholar

[12] A. Huang, Q. Xue, and J. Yang, in: WAIM, (2003).

Google Scholar

[13] A. Balmin, V. Hristidis and Y. Papakonstantinou, in: VLDB, (2004).

Google Scholar

[14] J. Coffman: The School of Engineering and Applied Science, (University of Virginia, 2012).

Google Scholar

[15] N. Zhang, I. F. Ilyas and M. T. Ozsu: Technical Report CiteSeer, (2011).

Google Scholar

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