Abstract
Point-of-interest (POI) querying, which searches and recommends visiting places for individuals with context constraints, has recently become a very popular location-based service. The existing approaches, however, mainly focus on finding a single POI instead of a group of POIs that are neibouring with each other. Some few approaches do handle the querying of collective POIs, but fail to consider users’ preference. In this paper, we devise a novel approach which aims to retrieve collective POIs based on multiple keywords given by a user as well as user preference, POI popularity and congestion. In addition, we design a cost function to calculate the visit cost of the candidate POIs. We also propose an efficient algorithm based on IR-tree which finds the optimal solution to achieve the balance between multiple optimization targets. The extensive experiments based on the real data from Toronto Canada demonstrate the effectiveness and efficiency of our approach.
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Cao, X., Cong, G., Guo, T., Jensen, C.S., Ooi, B.C.: Efficient processing of spatial group keyword queries. ACM Trans. Database Syst. 40(2), 13 (2015)
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)
Chan, H.K.H., Long, C., Wong, R.C.W.: On generalizing collective spatial keyword queries. IEEE Trans. Knowl. Data Eng. 30(9), 1712–1726 (2018)
Cho, H.J., Kwon, S.J., Chung, T.S.: ALPS: an efficient algorithm for top-k spatial preference search in road networks. Knowl. Inf. Syst. 42(3), 599–631 (2015)
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)
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)
Hong, H.J., Chiu, G.M., Tsai, W.Y.: A single quadtree-based algorithm for top-k spatial keyword query. Pervasive Mob. Comput. 42, 93–107 (2017)
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)
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)
Luo, S., Luo, Y., Zhou, S., Cong, G., Guan, J., Yong, Z.: Distributed spatial keyword querying on road networks. In: EDBT, pp. 235–246. Citeseer (2014)
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). https://doi.org/10.1007/978-3-642-22922-0_13
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)
Sun, J., Xu, J., Zheng, K., Liu, C.: Interactive spatial keyword querying with semantics. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp. 1727–1736. ACM (2017)
Wang, X., Zhang, Y., Zhang, W., Lin, X., Wang, W.: AP-tree: efficiently support continuous spatial-keyword queries over stream. In: Proceedings of the 2015 IEEE 31st International Conference on Data Engineering (ICDE), pp. 1107–1118. IEEE (2015)
Yuan, Y., Lian, X., Chen, L., Sun, Y., Wang, G.: RSkNN: kNN search on road networks by incorporating social influence. IEEE Trans. Knowl. Data Eng. 28(6), 1575–1588 (2016)
Zhang, D., Chee, Y.M., Mondal, A., Tung, A.K., Kitsuregawa, M.: Keyword search in spatial databases: towards searching by document. In: Proceedings of the 2009 IEEE 25th International Conference on Data Engineering (ICDE), pp. 688–699. IEEE (2009)
Zhang, D., Ooi, B.C., Tung, A.K.: Locating mapped resources in web 2.0. In: Proceedings of the 2010 IEEE 26th International Conference on Data Engineering (ICDE), pp. 521–532. IEEE (2010)
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Yu, D., Wu, Y., Liu, C., Sun, X. (2019). Collective POI Querying Based on Multiple Keywords and User Preference. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11447. Springer, Cham. https://doi.org/10.1007/978-3-030-18579-4_36
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