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PACOKS: Progressive Ant-Colony-Optimization-Based Keyword Search over Relational Databases

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Web-Age Information Management (WAIM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9659))

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Abstract

Keyword search over relational databases makes it easier to retrieve information from structural data. One solution is to first represent the relational data as a graph, and then find the minimum Steiner tree containing all the keywords by traversing the graph. However, the existing work involves substantial costs even for those based on heuristic algorithms, as the minimum Steiner tree problem is proved to be an NP-hard problem. In order to reduce the response time for a single search to a low level, a progressive ant-colony-optimization-based algorithm, called PACOKS, is proposed here, which achieves the best answer in a step-by-step manner, through the cooperation of large amounts of searches over time, instead of in an one-step manner by a single search. Through this way, the high costs for finding the best answer, are shared among large amounts of searches, so that low cost and fast response time for a single search is achieved. Extensive experimental results based on our prototype show that our method can achieve better performance than those state-of-the-art methods.

Supported by the Natural Science Foundation of China (61303004), the National Key Technology Support Program (2015BAH16F00/F01) and the Key Technology Program of Xiamen City (3502Z20151016).

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References

  1. Agrawal, S., Chaudhuri, S., Das, G.: DBXplorer: A system for keyword-based search over relational databases. In: Proceedings of ICDE, pp. 5–16 (2002)

    Google Scholar 

  2. Bhalotia, G., Hulgeri, A., Nakhe, C., Chakrabarti, S., Sudarshan, S.: Keyword searching and browsing in databases using banks. In: Proceedings of ICDE, pp. 431–440 (2002)

    Google Scholar 

  3. Djebali, S., Raimbault, T.: SimplePARQL: a new approach using keywords over SPARQL to query the web of data. In: Proceedings of the 11th International Conference on Semantic Systems, SEMANTICS 2015, Vienna, Austria, 15–17 September 2015, pp. 188–191 (2015)

    Google Scholar 

  4. Gutjahr, W.J.: A graph-based ant system and its convergence. Future Gener. Comput. Syst. 16(1), 873–888 (2000)

    Article  Google Scholar 

  5. He, H., Wang, H., Yang, J., Yu, P.S.: BLINKS: ranked keyword searches on graphs. In: Proceedings of SIGMOD, pp. 305–316 (2007)

    Google Scholar 

  6. Hristidis, V., Papakonstantinou, Y.: DISCOVER: Keyword search in relationaldatabases. In: Proceedings of VLDB, pp. 670–681 (2002)

    Google Scholar 

  7. Kacholia, V., Pandit, S., Chakrabarti, S., Sudarshan, S., Desai, R., Karambelkar, H.: Bidirectional expansion for keyword search on graph databases. In: Proceedings of VLDB, pp. 505–516 (2005)

    Google Scholar 

  8. Kim, I.-J., Whang, K.-Y., Kwon, H.-Y.: SRT-rank: Ranking keyword query results in relational databases using the strongly related tree. IEICE Trans. Inf. Syst. 97(D(9)), 2398–2414 (2014)

    Article  Google Scholar 

  9. Li, G., Ooi, B.C., Feng, J., Wang, J., Zhou, L.: EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data. In: Proceedings of SIGMOD, pp. 903–914 (2008)

    Google Scholar 

  10. Liu, F., Yu, C., Meng, W., Chowdhury, A.: Effective keyword search in relational databases. In: Proceedings of SIGMOD, pp. 563–574 (2006)

    Google Scholar 

  11. Luo, Y., Wang, W., Lin, X., Zhou, X., Wang, J., Li, K.: Spark2: Top-k keyword query in relational databases. TKDE 23(12), 1763–1780 (2011)

    Google Scholar 

  12. Markowetz, A., Yang, Y., Papadias, D.: Keyword search on relational data streams. In: Proceedings of SIGMOD, pp. 605–616 (2007)

    Google Scholar 

  13. Park, C.-S., Lim, S.: Effective keyword query processing with an extended answer structure in large graph databases. IJWIS 10(1), 65–84 (2014)

    Google Scholar 

  14. Tao, Y., Yu, J.X.: Finding frequent co-occurring terms in relational keyword search. In: Proceedings of EDBT, pp. 839–850 (2009)

    Google Scholar 

  15. Yang, W., Guo, T.: An ant colony optimization algorithm for the minimum steiner tree problem and its convergence proof. Acta Math. Appl. Sinica 29(2), 352–361 (2006)

    MathSciNet  Google Scholar 

  16. Zhou, J., Liu, Y., Yu, Z.: Improving the effectiveness of keyword search in databases using query logs. In: Li, J., Sun, Y., Yu, X., Sun, Y., Dong, X.L., Dong, X.L. (eds.) WAIM 2015. LNCS, vol. 9098, pp. 193–206. Springer, Heidelberg (2015). doi:10.1007/978-3-319-21042-1_16

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Xiamen University, Xiamen, China

    Ziyu Lin & Qian Xue

  2. School of Software, Xiamen University, Xiamen, China

    Yongxuan Lai

Authors
  1. Ziyu Lin
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  2. Qian Xue
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  3. Yongxuan Lai
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Corresponding author

Correspondence to Ziyu Lin .

Editor information

Editors and Affiliations

  1. Peking University , Beijing, China

    Bin Cui

  2. The George Washington University , Washington, D.C., USA

    Nan Zhang

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

  4. University of Texas Rio Grande Valley, Edinburg, Texas, USA

    Xiang Lian

  5. Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China

    Dexi Liu

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© 2016 Springer International Publishing Switzerland

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Lin, Z., Xue, Q., Lai, Y. (2016). PACOKS: Progressive Ant-Colony-Optimization-Based Keyword Search over Relational Databases. In: Cui, B., Zhang, N., Xu, J., Lian, X., Liu, D. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9659. Springer, Cham. https://doi.org/10.1007/978-3-319-39958-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-39958-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39957-7

  • Online ISBN: 978-3-319-39958-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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