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Effective Spatial Keyword Query Processing on Road Networks

  • Hailin Fang
  • Pengpeng Zhao
  • Victor S. Sheng
  • Jian Wu
  • Jiajie Xu
  • An Liu
  • Zhiming Cui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9093)

Abstract

Spatial keyword query plays an important role in many applications with rapid growth of spatio-textual objects collected. In this context, processing boolean spatial keyword query on road networks is one of the most interesting problems. When giving a query which contains a location and a group of keywords, our aim is to return \(k\) objects containing all the query keywords which are the nearest to the query location. Though the research on this problem has received extensive studies in Euclidean space, little is done to deal with it on road networks. We first propose novel indexing structures and algorithms that are able to process such query efficiently. Experimental results on multiple real-word datasets show that our methods achieves high performance.

Keywords

Road networks Spatial keyword search Spatial indexing 

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References

  1. 1.
    Cao, X., Chen, L., Cong, G., Jensen, C.S., Qu, Q., Skovsgaard, A., Wu, D., Yiu, M.L.: Spatial keyword querying. In: Atzeni, P., Cheung, D., Ram, S. (eds.) ER 2012 Main Conference 2012. LNCS, vol. 7532, pp. 16–29. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  2. 2.
    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
  3. 3.
    Chen, L., Cong, G., Jensen, C.S., Wu, D.: Spatial keyword query processing: an experimental evaluation. Proceedings of the VLDB Endowment 6(3), 217–228 (2013)CrossRefGoogle Scholar
  4. 4.
    De Felipe, I., Hristidis, V., Rishe, N.: Keyword search on spatial databases. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 656–665. IEEE (2008)Google Scholar
  5. 5.
    Jensen, C.S., Kolářvr, J., Pedersen, T.B., Timko, I.: Nearest neighbor queries in road networks. In: Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems, pp. 1–8. ACM (2003)Google Scholar
  6. 6.
    Lee, K.C., Lee, W.C., Zheng, B.: Fast object search on road networks. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, pp. 1018–1029. ACM (2009)Google Scholar
  7. 7.
    Lee, K.C., Lee, W.C., Zheng, B., Tian, Y.: Road: a new spatial object search framework for road networks. IEEE Transactions on Knowledge and Data Engineering 24(3), 547–560 (2012)CrossRefGoogle Scholar
  8. 8.
    Li, W., Guan, J., Zhou, S.: Efficiently evaluating range-constrained spatial keyword query on road networks. In: Han, W.-S., Lee, M.L., Muliantara, A., Sanjaya, N.A., Thalheim, B., Zhou, S. (eds.) DASFAA 2014. LNCS, vol. 8505, pp. 283–295. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  9. 9.
    Papadias, D., Zhang, J., Mamoulis, N., Tao, Y.: Query processing in spatial network databases. In: Proceedings of the 29th International Conference on Very Large Data Bases, vol. 29, pp. 802–813. VLDB Endowment (2003)Google Scholar
  10. 10.
    Rocha-Junior, J.B., Nørvåg, K.: Top-k spatial keyword queries on road networks. In: Proceedings of the 15th International Conference on Extending Database Technology, pp. 168–179. ACM (2012)Google Scholar
  11. 11.
    Samet, H., Sankaranarayanan, J., Alborzi, H.: Scalable network distance browsing in spatial databases. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 43–54. ACM (2008)Google Scholar
  12. 12.
    Shekhar, S., Liu, D.R.: Ccam: A connectivity-clustered access method for networks and network computations. IEEE Transactions on Knowledge and Data Engineering 9(1), 102–119 (1997)CrossRefGoogle Scholar
  13. 13.
    Zhang, C., Zhang, Y., Zhang, W., Lin, X.: Inverted linear quadtree: efficient top k spatial keyword search. In: 2013 IEEE 29th International Conference on Data Engineering (ICDE), pp. 901–912. IEEE (2013)Google Scholar
  14. 14.
    Zhang, D., Tan, K.L., Tung, A.K.: Scalable top-k spatial keyword search. In: Proceedings of the 16th International Conference on Extending Database Technology, pp. 359–370. ACM (2013)Google Scholar
  15. 15.
    Zhong, R., Li, G., Tan, K.L., Zhou, L.: G-tree: an efficient index for knn search on road networks. In: Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management, pp. 39–48. ACM (2013)Google Scholar
  16. 16.
    Zhou, Y., Xie, X., Wang, C., Gong, Y., Ma, W.Y.: Hybrid index structures for location-based web search. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 155–162. ACM (2005)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hailin Fang
    • 1
  • Pengpeng Zhao
    • 1
  • Victor S. Sheng
    • 2
  • Jian Wu
    • 1
  • Jiajie Xu
    • 1
  • An Liu
    • 1
  • Zhiming Cui
    • 1
  1. 1.School of Computer Science and TechnologySoochow UniversitySuzhouPeople’s Republic of China
  2. 2.Computer Science DepartmentUniversity of Central ArkansasConwayUSA

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