Abstract
Nowadays many devices and applications in social networks and location-based services are producing, storing and using description, location and occurrence time of objects. Given a massive number of boolean top-k spatial-temporal queries and the spatial-textual message streams, in this paper we study the problem of continuously updating top-k messages with the highest ranks, each of which contains all the requested keywords when rank of a message is calculated by its location and freshness. Decreasing the ranks of existing top-k results over time and producing new incoming messages, cause continuously computing and maintaining the best results. To the best of our knowledge, there is no prior work that can exactly solve this problem. We propose two indexing and matching methods, then conduct an experimental evaluation to show the impact of parameters and analyse the models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen, L., Cong, G., Cao, X.: An efficient query indexing mechanism for filtering geo-textual data. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 749–760 (2013)
Chen, L., Cong, G., Cao, X., Tan, K.L.: Temporal spatial-keyword top-k publish/subscribe. In: Proceedings - International Conference on Data Engineering, pp. 255–266 (2015)
Chen, L., Cong, G., Jensen, C., Wu, D.: Spatial keyword query processing: an experimental evaluation. PVLDB 6(3), 217–228 (2013)
Choudhury, F.M., Culpepper, J.S., Sellis, T.: Batch processing of top-k spatial-textual queries. In: Second International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data, pp. 7–12 (2015)
Christoforaki, M., He, J., Dimopoulos, C., Markowetz, A., Suel, T.: Text vs. space: efficient geo-search query processing. In: 20th ACM International Conference on Information and Knowledge Management, pp. 423–432 (2011)
Efron, M., Golovchinsky, G.: Estimation methods for ranking recent information. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 495–504. ACM (2011)
Guo, L., Zhang, D., Li, G., Tan, K.-L., Bao, Z.: Location-aware pub/sub system: when continuous moving queries meet dynamic event streams. In: SIGMOD, pp. 843–857 (2015)
Hmedeh, Z., Kourdounakis, H., Christophides, V., du Mouza, C., Scholl, M., Travers, N.: Content-based publish/subscribe system for web syndication. J. Comput. Sci. Technol. 31(2), 359–380 (2016)
Ray, S., Nickerson, B.G.: Dynamically ranked top-k spatial keyword search. In: Proceedings of the Third International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data (2016)
Samet, H.: The quadtree and related hierarchical data structures. ACM Comput. Surv. 16(2), 187–260 (1984)
Wang, X., Zhang, Y., Zhang, W., Lin, X., Huang, Z.: SKYPE: top-k spatial-keyword publish/subscribe over sliding window. Proc. VLDB Endow. 9(7), 588–599 (2016)
Wang, X., Zhang, Y., Zhang, W., Lin, X., Wang, W.: AP-tree: efficiently support continuous spatial-keyword queries over stream. In: 31st International Conference on Data Engineering, pp. 1107–1118. IEEE (2015)
Yu, M.: A cost-based method for location-aware publish/subscribe services. CIKM 1, 693–702 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Ghafouri, M., Wang, X., Yuan, L., Zhang, Y., Lin, X. (2018). Maintaining Boolean Top-K Spatial Temporal Results in Publish-Subscribe Systems. In: Wang, J., Cong, G., Chen, J., Qi, J. (eds) Databases Theory and Applications. ADC 2018. Lecture Notes in Computer Science(), vol 10837. Springer, Cham. https://doi.org/10.1007/978-3-319-92013-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-92013-9_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92012-2
Online ISBN: 978-3-319-92013-9
eBook Packages: Computer ScienceComputer Science (R0)