Retrieving Text-Based Surrounding Objects in Spatial Databases

  • Bojie ShenEmail author
  • Md. Saiful Islam
  • David Taniar
  • Junhu Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)


Retrieval of textually relevant non-dominated surrounding data objects has many potential applications in spatial databases such as textually relevant nearby point-of-interest retrieval surrounding a user. This paper presents a novel query, called textually-relevant direction-based spatial skyline (TDSS), for retrieving textually relevant non-dominated surrounding data objects in spatial databases. The paper also presents efficient algorithms for processing TDSS queries in spatial databases by designing novel data pruning techniques using keyword inverted index and R-Tree data indexing scheme. The effectiveness and efficiency of the proposed algorithms are demonstrated by conducting extensive experiments.



This work was partially supported by a Griffith University’s 2018 New Researcher Grant with Dr. Md Saiful Islam being the Chief Investigator. The first and second authors contributed equally in this paper.


  1. 1.
    Borzsony, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)Google Scholar
  2. 2.
    Cao, X., Chen, L., Cong, G., Jensen, C.S., Qu, Q., Skovsgaard, A., Wu, D., Yiu, M.L.: Spatial keyword querying. In: ER, pp. 16–29 (2012)Google Scholar
  3. 3.
    Cary, A., Wolfson, O., Rishe, N.: Efficient and scalable method for processing top-k spatial boolean queries. In: SSDBM, pp. 87–95 (2010)Google Scholar
  4. 4.
    Chan, C.Y., Jagadish, H.V., Tan, K., Tung, A.K.H., Zhang, Z.: Finding k-dominant skylines in high dimensional space. In: SIGMOD, pp. 503–514 (2006)Google Scholar
  5. 5.
    Dellis, E., Seeger, B.: Efficient computation of reverse skyline queries. In: VLDB, pp. 291–302 (2007)Google Scholar
  6. 6.
    Felipe, I.D., Hristidis, V., Rishe, N.: Keyword search on spatial databases. In: ICDE, pp. 656–665 (2008)Google Scholar
  7. 7.
    Guo, X., Ishikawa, Y., Gao, Y.: Direction-based spatial skylines. In: MobiDE, pp. 73–80 (2010)Google Scholar
  8. 8.
    Guo, X., Zheng, B., Ishikawa, Y., Gao, Y.: Direction-based surrounder queries for mobile recommendations. VLDB J. 20(5), 743–766 (2011)CrossRefGoogle Scholar
  9. 9.
    Islam, M.S., Liu, C.: Know your customer: computing k-most promising products for targeted marketing. VLDB J. 25(4), 545–570 (2016)CrossRefGoogle Scholar
  10. 10.
    Islam, M.S., Liu, C., Rahayu, J.W., Anwar, T.: Q+Tree: an efficient quad tree based data indexing for parallelizing dynamic and reverse skylines. In: CIKM, pp. 1291–1300 (2016)Google Scholar
  11. 11.
    Islam, M.S., Rahayu, J.W., Liu, C., Anwar, T., Stantic, B.: Computing influence of a product through uncertain reverse skyline. In: SSDBM, pp. 4:1–4:12 (2017)Google Scholar
  12. 12.
    Islam, M.S., Zhou, R., Liu, C.: On answering why-not questions in reverse skyline queries. In: ICDE, pp. 973–984 (2013)Google Scholar
  13. 13.
    Lee, K.C.K., Lee, W., Leong, H.V.: Nearest surrounder queries. IEEE Trans. Knowl. Data Eng. 22(10), 1444–1458 (2010)CrossRefGoogle Scholar
  14. 14.
    Lee, K.C.K., Schiffman, J., Zheng, B., Lee, W., Leong, H.V.: Tracking nearest surrounders in moving object environments. In: ICPS, pp. 3–12 (2006)Google Scholar
  15. 15.
    Lee, M.W., Son, W., Ahn, H.K., Hwang, S.W.: Spatial skyline queries: exact and approximation algorithms. GeoInformatica 15(4), 665–697 (2011)CrossRefGoogle Scholar
  16. 16.
    Li, F., Cheng, D., Hadjieleftheriou, M., Kollios, G., Teng, S.: On trip planning queries in spatial databases. In: SSTD, pp. 273–290 (2005)Google Scholar
  17. 17.
    Lin, Q., Zhang, Y., Zhang, W., Li, A.: General spatial skyline operator. In: DASFAA, pp. 494–508 (2012)Google Scholar
  18. 18.
    Lin, X., Yuan, Y., Zhang, Q., Zhang, Y.: Selecting stars: the k most representative skyline operator. In: ICDE, pp. 86–95 (2007)Google Scholar
  19. 19.
    Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: SIGMOD, pp. 467–478 (2003)Google Scholar
  20. 20.
    Rocha-Junior, J.B., Gkorgkas, O., Jonassen, S., Nørvåg, K.: Efficient processing of top-k spatial keyword queries. In: SSTD, pp. 205–222 (2011)Google Scholar
  21. 21.
    Sharifzadeh, M., Shahabi, C.: The spatial skyline queries. In: VLDB, pp. 751–762 (2006)Google Scholar
  22. 22.
    Shi, J., Wu, D., Mamoulis, N.: Textually relevant spatial skylines. IEEE Trans. Knowl. Data Eng. 28(1), 224–237 (2016)CrossRefGoogle Scholar
  23. 23.
    Sohail, A., Cheema, M.A., Taniar, D.: Social-aware spatial top-k and skyline queries. Comput. J. 61(11), 1620–1638 (2018)MathSciNetGoogle Scholar
  24. 24.
    Son, W., Lee, M.W., Ahn, H.K., Hwang, S.W.: Spatial skyline queries: an efficient geometric algorithm. In: SSTD, pp. 247–264. Springer (2009)Google Scholar
  25. 25.
    Wu, D., Yiu, M.L., Cong, G., Jensen, C.S.: Joint top-k spatial keyword query processing. IEEE Trans. Knowl. Data Eng. 24(10), 1889–1903 (2012)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Bojie Shen
    • 1
    Email author
  • Md. Saiful Islam
    • 2
  • David Taniar
    • 1
  • Junhu Wang
    • 2
  1. 1.Monash UniversityMelbourneAustralia
  2. 2.Griffith UniversityGold CoastAustralia

Personalised recommendations