Advertisement

Preference-Aware Top-k Spatio-Textual Queries

  • Yunpeng GaoEmail author
  • Yao Wang
  • Shengwei Yi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9998)

Abstract

A novel query type named preference-aware top-k spatial-textual query is proposed in this paper. Unlike the common measure, this query returns spatial-textual objects ranked according to the warefare of the facilities in conditional range. Suppose a tourist that looks for motels that have nearby a highly rated Japanese restaurant that serves sushi. The proposed query considers not only the spatial location and textual description of spatial-textual objects (such as motels and restaurants), but also additional information such as ratings that describe their quality. Furthermore, spatial-textual objects (i.e., motels) are ranked according to the features of facilities (i.e., restaurants) in their neighborhood. However, it is time-consuming to compute the score of data object. To address this issue, we propose an efficient algorithm for processing this query. Last but not least, we conduct extensive experiments for evaluating the performance of the proposed methods.

References

  1. 1.
    Bouros, P., Ge, S., Mamoulis, N.: Spatio-textual similarity joins. Proc. VLDB Endowment 6(1), 1–12 (2012)CrossRefGoogle Scholar
  2. 2.
    Cao, C.C., Tong, Y., Chen, L., Jagadish, H.V.: Wisemarket: a new paradigm for managing wisdom of online social users. In: SIGKDD 2013, pp. 455–463 (2013)Google Scholar
  3. 3.
    Cao, X., Cong, G., Jensen, C.S.: Retrieving top-k prestige-based relevant spatial web objects. Proc. VLDB Endowment 3(1–2), 373–384 (2010)CrossRefGoogle Scholar
  4. 4.
    Chen, L., Cong, G., Jensen, C.S., Wu, D.: Spatial keyword query processing: an experimental evaluation. Proc. VLDB Endowment. 6, 217–228 (2013)CrossRefGoogle Scholar
  5. 5.
    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
  6. 6.
    De Felipe, I., Hristidis, V., Rishe, N.: Keyword search on spatial databases. In: ICDE 2008, pp. 656–665 (2008)Google Scholar
  7. 7.
    Li, Z., Lee, K.C., Zheng, B., Lee, W.C., Lee, D., Wang, X.: Ir-tree: an efficient index for geographic document search. IEEE Trans. Knowl. Data Eng. 23(4), 585–599 (2011)CrossRefGoogle Scholar
  8. 8.
    Rocha-Junior, J.B., Gkorgkas, O., Jonassen, S., Nørvåg, K.: Efficient processing of top-k spatial keyword queries. In: Pfoser, D., Tao, Y., Mouratidis, K., Nascimento, M.A., Mokbel, M., Shekhar, S., Huang, Y. (eds.) SSTD 2011. LNCS, vol. 6849, pp. 205–222. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Rocha-Junior, J.B., Vlachou, A., Doulkeridis, C., Nørvåg, K.: Efficient processing of top-k spatial preference queries. Proc. VLDB Endowment 4(2), 93–104 (2010)CrossRefGoogle Scholar
  10. 10.
    She, J., Tong, Y., Chen, L.: Utility-aware social event-participant planning. In: SIGMOD 2015, pp. 1629–1643 (2015)Google Scholar
  11. 11.
    She, J., Tong, Y., Chen, L., Cao, C.C.: Conflict-aware event-participant arrangement. In: ICDE 2015, pp. 735–746 (2015)Google Scholar
  12. 12.
    She, J., Tong, Y., Chen, L., Cao, C.C.: Conflict-aware event-participant arrangement and its variant for online setting. IEEE Trans. Knowl. Data Eng. 28(9), 2281–2295 (2016)CrossRefGoogle Scholar
  13. 13.
    Tong, Y., Cao, C.C., Chen, L.: TCS: efficient topic discovery over crowd-oriented service data. In: SIGKDD 2014, pp. 861–870 (2014)Google Scholar
  14. 14.
    Tong, Y., Cao, C.C., Zhang, C.J., Li, Y., Chen, L.: Crowdcleaner: data cleaning for multi-version data on the web via crowdsourcing. In: ICDE 2014, pp. 1182–1185 (2014)Google Scholar
  15. 15.
    Tong, Y., She, J., Ding, B., Chen, L., Wo, T., Xu, K.: Online minimum matching in real-time spatial data: experiments and analysis. Proc. VLDB Endowment 9(12), 1053–1064 (2016)CrossRefGoogle Scholar
  16. 16.
    Tong, Y., She, J., Ding, B., Wang, L., Chen, L.: Online mobile micro-task allocation in spatial crowdsourcing. In: ICDE 2016, pp. 49–60 (2016)Google Scholar
  17. 17.
    Tong, Y., She, J., Meng, R.: Bottleneck-aware arrangement over event-based social networks: the max-min approach. World Wide Web J. 19(6), 1151–1177 (2016)CrossRefGoogle Scholar
  18. 18.
    Yiu, M.L., Dai, X., Mamoulis, N., Vaitis, M.: Top-k spatial preference queries. In: ICDE 2007, pp. 1076–1085 (2007)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.State Key Laboratory of Software Development Environment, Beihang UniversityBeijingChina
  2. 2.Yellow River Engineering Consulting Co., Ltd.ZhengzhouChina
  3. 3.China Information Technology Security Evaluation CenterBeijingChina

Personalised recommendations