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Reverse Collective Spatial Keyword Querying (Short Paper)

  • Yang WuEmail author
  • Jian Xu
  • Liming Tu
  • Ming Luo
  • Zhi Chen
  • Ning Zheng
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 268)

Abstract

Recently, Collective Spatial Keyword Querying (CoSKQ), which returns a group of objects that cover a set of given keywords collectively and have the smallest cost, has received extensive attention in spatial database community. However, no research so far focuses on a situation when the result of CoSKQ is taken as the input of a query. But this kind of query has many applications in location based services. In this paper, we introduce a new problem Reverse Collective Spatial Keyword Querying (RCoSKQ) that returns a region, in which the query objects are qualified objects with the highest spatial and textual similarity. We propose an efficient method which uses IR-tree to retrieve objects with text descriptions. To accelerate the query process, a pruning method that effectively reduces computing is proposed. The experiments over real and synthesis data sets demonstrate the efficiency of our approaches.

Keywords

Collective Spatial Keyword Querying A set of query objects Reverse 

Notes

Acknowledgment

This work is supported by the National Natural Science Foundation of China (No. 61572165), the Natural Science Foundation of Zhejiang Province (No. LZ15F 020003).

References

  1. 1.
    Cao, X., Cong, G., Jensen, C.S., Ooi, B.C.: Collective spatial keyword querying. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 373–384. ACM (2011)Google Scholar
  2. 2.
    Cheema, M.A., Lin, X., Zhang, W., Zhang, Y.: Influence zone: efficiently processing reverse k nearest neighbors queries. In: 2011 IEEE 27th International Conference on Data Engineering (ICDE), pp. 577–588. IEEE (2011)Google Scholar
  3. 3.
    Choudhury, F.M., Culpepper, J.S., Sellis, T., Cao, X.: Maximizing bichromatic reverse spatial and textual k nearest neighbor queries. Proc. VLDB Endowment 9(6), 456–467 (2016)CrossRefGoogle Scholar
  4. 4.
    Cong, G., Jensen, C.S., Wu, D.: Efficient retrieval of the top-k most relevant spatial web objects. Proc. VLDB Endowment 2(1), 337–348 (2009)CrossRefGoogle Scholar
  5. 5.
    Fang, H., et al.: Ranked reverse boolean spatial keyword nearest neighbors search. In: Wang, J., et al. (eds.) WISE 2015. LNCS, vol. 9418, pp. 92–107. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-26190-4_7CrossRefGoogle Scholar
  6. 6.
    Gao, Y., Qin, X., Zheng, B., Chen, G.: Efficient reverse top-k boolean spatial keyword queries on road networks. IEEE Trans. Knowl. Data Eng. 27(5), 1205–1218 (2015)CrossRefGoogle Scholar
  7. 7.
    Gao, Y., Zhao, J., Zheng, B., Chen, G.: Efficient collective spatial keyword query processing on road networks. IEEE Trans. Intell. Transp. Syst. 17(2), 469–480 (2016)CrossRefGoogle Scholar
  8. 8.
    Long, C., Wong, R.C.W., Wang, K., Fu, A.W.C.: Collective spatial keyword queries: a distance owner-driven approach. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 689–700. ACM (2013)Google Scholar
  9. 9.
    Lu, J., Lu, Y., Cong, G.: Reverse spatial and textual k nearest neighbor search. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 349–360. ACM (2011)Google Scholar
  10. 10.
    Tao, Y., Papadias, D., Lian, X.: Reverse kNN search in arbitrary dimensionality. In: Proceedings of the Thirtieth International Conference on Very Large Data Bases-Volume 30, pp. 744–755. VLDB Endowment (2004)Google Scholar
  11. 11.
    Wei, W., Yang, F., Chan, C.-Y., Tan, K.-L.: FINCH: evaluating reverse k-nearest-neighbor queries on location data. Proc. VLDB Endowment 1(1), 1056–1067 (2008)CrossRefGoogle Scholar
  12. 12.
    Xie, X., Lin, X., Xu, J., Jensen, C.S.: Reverse keyword-based location search. In: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), pp. 375–386. IEEE (2017)Google Scholar
  13. 13.
    Yang, S., Cheema, M.A., Lin, X., Zhang, Y.: SLICE: reviving regions-based pruning for reverse k nearest neighbors queries. In: 2014 IEEE 30th International Conference on Data Engineering (ICDE), pp. 760–771. IEEE (2014)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Yang Wu
    • 1
    Email author
  • Jian Xu
    • 1
  • Liming Tu
    • 1
  • Ming Luo
    • 1
  • Zhi Chen
    • 1
  • Ning Zheng
    • 1
  1. 1.School of Computer Science and TechnologyHangzhou Dianzi UniversityHangzhouChina

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