Skip to main content
SpringerLink
Log in

Shadow: Answering Why-Not Questions on Top-K Spatial Keyword Queries over Moving Objects

  • Conference paper
  • First Online:
Database Systems for Advanced Applications (DASFAA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12682))

Included in the following conference series:

Abstract

The popularity of mobile terminals has generated massive moving objects with spatio-textual characteristics. A top-k spatial keyword query over moving objects (Top-k SKM query) returns the top-k objects, moving or static, based on a ranking function that considers spatial distance and textual similarity between the query and objects. To the best of our knowledge, there hasn’t been any research into the why-not questions on Top-k SKM queries. Aiming at this kind of why-not questions, a two-level index called Shadow and a three-phase query refinement approach based on Shadow are proposed. The first phase is to generate some promising refined queries with different query requirements and filter those unpromising refined queries before executing any promising refined queries. The second phase is to reduce the irrelevant search space in the level 1 of Shadow as much as possible based on the spatial filtering technique, so as to obtain the promising static objects, and to capture promising moving objects in the level 2 of Shadow as fast as possible based on the probability filtering technique. The third phase is to determine which promising refined query will be returned to the user. Finally, a series of experiments are conducted on three datasets to verify the feasibility of our method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.geonames.org/.

References

  1. Cao, B., et al.: SIMkNN: a scalable method for in-memoryknn search over moving objects in road networks. IEEE Trans. Knowl. Data Eng. 30(10), 1957–1970 (2018)

    Article  Google Scholar 

  2. Chapman, A., Jagadish, H.V.: Why not. In: Proceedings Acm Sigmod, pp. 523–534 (2009)

    Google Scholar 

  3. Chen, L., Li, Y., Xu, J., Jensen, C.S.: Direction-aware why-not spatial keyword top-k queries. In: Proceedings of the IEEE 33rd International Conference on Data Engineering, pp. 107–110 (2017)

    Google Scholar 

  4. Chen, L., Lin, X., Hu, H., Jensen, C.S., Xu, J.: Answering why-not questions on spatial keyword top-k queries. In: Proceedings of the IEEE 31st International Conference on Data Engineering, pp. 279–290 (2015)

    Google Scholar 

  5. Chen, L., Xu, J., Lin, X., Jensen, C.S., Hu, H.: Answering why-not spatial keyword top-k queries via keyword adaption. In: Proceedings of the IEEE 32nd International Conference on Data Engineering, pp. 697–708 (2016)

    Google Scholar 

  6. Chen, L., Shang, S., Zheng, K., Kalnis, P.: Cluster-based subscription matching for geo-textual data streams. In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 890–901 (2019)

    Google Scholar 

  7. Cui, N., Li, J., Yang, X., Wang, B., Reynolds, M., Xiang, Y.: When geo-text meets security: privacy-preserving boolean spatial keyword queries. In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 1046–1057 (2019)

    Google Scholar 

  8. Dittrich, J., Blunschi, L., Vaz Salles, M.A.: Indexing moving objects using short-lived throwaway indexes. In: Mamoulis, N., Seidl, T., Pedersen, T.B., Torp, K., Assent, I. (eds.) SSTD 2009. LNCS, vol. 5644, pp. 189–207. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02982-0_14

    Chapter  Google Scholar 

  9. Tianyang, D., Lulu, Y., Qiang, C., Bin, C., Jing, F.: Direction-aware KNN queries for moving objects in a road network. World Wide Web 22(4), 1765–1797 (2019). https://doi.org/10.1007/s11280-019-00657-1

    Article  Google Scholar 

  10. He, Z., Lo, E.: Answering why-not questions on top-k queries. In: Proceedings of the IEEE 28th International Conference on Data Engineering, pp. 750–761 (2012)

    Google Scholar 

  11. Heendaliya, L., Wisely, M., Lin, D., Sarvestani, S.S., Hurson, A.R.: Indexing and querying techniques for moving objects in both euclidean space and road network. Adv. Comput. 102, 111–170 (2016)

    Article  Google Scholar 

  12. Li, Z., Lee, K.C.K., Zheng, B., Lee, W., Lee, D.L., Wang, X.: Ir-tree: an efficient index for geographic document search. IEEE Trans. Knowl. Data Eng. 23(4), 585–599 (2011)

    Article  Google Scholar 

  13. Liu, Q., Gao, Y.: Survey of database usability for query results. J. Comput. Res. Dev. 54(6), 1198–1212 (2017)

    Google Scholar 

  14. Miao, X., Gao, Y., Guo, S., Chen, G.: On efficiently answering why-not range-based skyline queries in road networks (extended abstract). In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 2131–2132 (2019)

    Google Scholar 

  15. Salgado, C., Cheema, M.A., Ali, M.E.: Continuous monitoring of range spatial keyword query over moving objects. World Wide Web 21(3), 687–712 (2017). https://doi.org/10.1007/s11280-017-0488-3

    Article  Google Scholar 

  16. Shen, B., et al.: V-tree: efficient knn search on moving objects with road-network constraints. In: Proceedings of the IEEE 33rd International Conference on Data Engineering, pp. 609–620 (2017)

    Google Scholar 

  17. Su, S., Teng, Y., Cheng, X., Xiao, K., Li, G., Chen, J.: Privacy-preserving top-k spatial keyword queries in untrusted cloud environments. IEEE Trans. Serv. Comput. 11(5), 796–809 (2018)

    Google Scholar 

  18. Wang, M., Liu, J., Wei, B., Yao, S., Zeng, H., Shi, L.: Answering why-not questions on SPARQL queries. Knowl. Inform. Syst. 58(1), 169–208 (2018). https://doi.org/10.1007/s10115-018-1155-4

    Article  Google Scholar 

  19. Wu, D., Choi, B., Xu, J., Jensen, C.S.: Authentication of moving top-k spatial keyword queries. IEEE Trans. Knowl. Data Eng. 27(4), 922–935 (2015)

    Article  Google Scholar 

  20. Xu, J., Güting, R.H., Zheng, Y., Wolfson, O.: Moving objects with transportation modes: a survey. J. Comput. Sci. Technol. 34(4), 709–726 (2019)

    Article  Google Scholar 

  21. Yang, J., Zhang, Y., Zhou, X., Wang, J., Hu, H., Xing, C.: A hierarchical framework for top-k location-aware error-tolerant keyword search. In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 986–997 (2019)

    Google Scholar 

  22. Yao, D., Cong, G., Zhang, C., Bi, J.: Computing trajectory similarity in linear time: a generic seed-guided neural metric learning approach. In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 1358–1369 (2019)

    Google Scholar 

  23. Zhang, C., Zhang, Y., Zhang, W., Lin, X.: Inverted linear quadtree: efficient top k spatial keyword search. In: Proceedings of the IEEE 29th International Conference on Data Engineering, pp. 901–912 (2013)

    Google Scholar 

  24. Zhang, D., Tan, K.L., Tung, A.K.H.: Scalable top-k spatial keyword search. In: Proceedings of the ACM 16th International Conference EDBT, pp. 359–370 (2013)

    Google Scholar 

  25. Zhao, J., Gao, Y., Chen, G., Chen, R.: Why-not questions on top-k geo-social keyword queries in road networks. In: Proceedings of the IEEE 34th International Conference on Data Engineering, pp. 965–976 (2018)

    Google Scholar 

  26. Zheng, B., et al.: Answering why-not group spatial keyword queries (extended abstract). In: Proceedings of the IEEE 35th International Conference on Data Engineering, pp. 2155–2156 (2019)

    Google Scholar 

  27. Zong, C., Wang, B., Sun, J., Yang, X.: Minimizing explanations of why-not questions. In: Han, W.-S., Lee, M.L., Muliantara, A., Sanjaya, N.A., Thalheim, B., Zhou, S. (eds.) DASFAA 2014. LNCS, vol. 8505, pp. 230–242. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-43984-5_17

    Chapter  Google Scholar 

Download references

Acknowledgments

This research is supported by Natural Science Foundation of China (Grant No.61572215), Natural Science Foundation of Hubei Province of China (Grant No.2017CFB135), the Ministry of education of Humanities and Social Science project of China (Grant No.20YJCZH111), and the Fundamental Research Funds for the Central Universities (CCNU: Grant No. CCNU20ZT013).

Author information

Authors and Affiliations

  1. College of Computer Science, South-Central University for Nationalities, Wuhan, China

    Wang Zhang & Yanhong Li

  2. College of Management, National Cheng Kung University, Taiwan, Republic of China

    Lihchyun Shu

  3. School of Computer, Central China Normal University, Wuhan, China

    Changyin Luo

  4. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Jianjun Li

Authors
  1. Wang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanhong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lihchyun Shu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Changyin Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jianjun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanhong Li .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Christian S. Jensen

  2. Singapore Management University, Singapore, Singapore

    Ee-Peng Lim

  3. Academia Sinica, Taipei, Taiwan

    De-Nian Yang

  4. The Pennsylvania State University, University Park, PA, USA

    Wang-Chien Lee

  5. National Chiao Tung University, Hsinchu, Taiwan

    Vincent S. Tseng

  6. Athens University of Economics and Business, Athens, Greece

    Vana Kalogeraki

  7. National Cheng Kung University, Tainan City, Taiwan

    Jen-Wei Huang

  8. National Tsing Hua University, Hsinchu, Taiwan

    Chih-Ya Shen

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, W., Li, Y., Shu, L., Luo, C., Li, J. (2021). Shadow: Answering Why-Not Questions on Top-K Spatial Keyword Queries over Moving Objects. In: Jensen, C.S., et al. Database Systems for Advanced Applications. DASFAA 2021. Lecture Notes in Computer Science(), vol 12682. Springer, Cham. https://doi.org/10.1007/978-3-030-73197-7_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-73197-7_51

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73196-0

  • Online ISBN: 978-3-030-73197-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation