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Research on Fuzzy Matching Query Algorithm Based on Spatial Multi-keyword

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Data Science (ICPCSEE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 727))

Abstract

With the rapid growth of spatial data, POI (Point of Interest) is becoming ever more intensive, and the text description of each spatial point is also gradually increasing. The traditional query method can only address the problem that the text description is less and single keyword query. In view of this situation, the paper proposes an approximate matching algorithm to support spatial multi-keyword. The fuzzy matching algorithm is integrated into this algorithm, which not only supports multiple POI queries, but also supports fault tolerance of the query keywords. The simulation results demonstrate that the proposed algorithm can improve the accuracy and efficiency of query.

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References

  1. Liu, X.P., Wan, C.X., Liu, D.X.: Survey on spatial keyword search. J. Softw. 27(2), 329–347 (2016)

    MathSciNet  Google Scholar 

  2. Yao, B., Li, F.F., Hadjieleftheriou, M.: Approximate string search in spatial databases. In: Proceedings of ICDE, pp. 545–556. IEEE, Washington (2010)

    Google Scholar 

  3. Alsubaiee, S., Behm, A., Li, C.: Supporting location-based approximate-keyword queries. In: Proceedings of SIGSPATIAL GIS, pp. 61–70. ACM Press, New York (2010)

    Google Scholar 

  4. Wang, J.B., Gao, H., Li, J.Z.: An index supporting spatial approximate keyword search on disks. J. Comput. Res. Dev. 49(10), 2142–2152 (2012)

    Google Scholar 

  5. Hu, J., Fan, J., Li, G.L., et al.: Top-k fuzzy spatial keyword search. Chin. J. Comput. 35(11), 2237–2246 (2012)

    Article  Google Scholar 

  6. Zhang, D.X., Chen, Y.M., Mondal, A., et al.: Keyword search in spatial databases: towards searching by document. In: Proceeding of 2009 IEEE International Conference Data Engineering, pp. 688–699. IEEE, Computer Society, Washington, DC (2009)

    Google Scholar 

  7. Cao, X., Cong, G., Ji, L., et al.: Collective spatial keyword querying. In: Proceedings of 2011 ACM SIGMOD, International Conference on Management of Data, pp. 373–384. ACM, New York (2011)

    Google Scholar 

  8. Long, C., Wong, R.C., Wang, K., et al.: Collective spatial keyword queries: a distance owner-driven approach. In: Proceedings of 2013 ACM SIGMOD International Conference on Management of Data, pp. 689–700. ACM, New York (2013)

    Google Scholar 

  9. Fan, J., Li, G.L., Zhou, L.Z., et al.: Seal: spatio-textual similarity search. Proc. VLDB Endow. 5(9), 824–835 (2012)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, Henan, China

    Suzhi Zhang, Yanan Zhao & Rui Yang

Authors
  1. Suzhi Zhang
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  2. Yanan Zhao
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  3. Rui Yang
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Corresponding author

Correspondence to Suzhi Zhang .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Beiji Zou

  2. Central South University, Changsha, China

    Min Li

  3. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  4. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  5. Harbin University of Science and Technology, Harbin, China

    Wei Xie

  6. Harbin Sea of Clouds and Computer Technology, Harbin, China

    Zeguang Lu

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© 2017 Springer Nature Singapore Pte Ltd.

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Zhang, S., Zhao, Y., Yang, R. (2017). Research on Fuzzy Matching Query Algorithm Based on Spatial Multi-keyword. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_11

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  • DOI: https://doi.org/10.1007/978-981-10-6385-5_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6384-8

  • Online ISBN: 978-981-10-6385-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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