Abstract
Preference queries serve for retrieving a small set of tuples with top aggregated scores over multiple features, from a large set of tuples. We consider the problem of maintaining the ranking lists of items for preference queries in dynamic virtual environments, which is very useful for avatars in virtual environments to continuously monitor interesting items surrounding them. Traditional solutions on preference queries utilize the pre-computed materialized ranking lists to efficiently find top items by only retrieving a prefix of the ranking lists. However, for preference queries in virtual environments, items (tuples) to be ranked change frequently due to the movements and updates of avatars. Creating and maintaining materialized ranking lists in such dynamic scenarios will be extremely expensive. In this paper, we address the problem by proposing a solution as a marriage of continuous range query and continuous top-k query. A preference query is continuously processed by dynamically adding and removing the perceived items of an avatar. Extensive experimental studies show that the proposed techniques are very efficient in handling the continuous updates of ranking lists.
Supported by the Fundamental Research Funds for the Central Universities, the Research Funds of Renmin University of China No. 14XNLQ06.
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
Bruno, N., Gravano, L., Marian, A.: Evaluating top-k queries over web-accessible databases. In: ICDE, pp. 369–380 (2002)
Cai, Y., Li, Q., Xie, H., Min, H.: Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy. Neural Netw. 58, 98–110 (2014)
Chen, Y., Cui, B., Du, X., Tung, A.K.H.: Efficient approximation of the maximal preference scores by lightweight cubic views. In: EDBT, pp. 240–251 (2012)
Das, G., Gunopulos, D., Koudas, N., Sarkas, N.: Ad-hoc top-k query answering for data streams. In: VLDB, pp. 183–194 (2007)
Das, G., Gunopulos, D., Koudas, N., Tsirogiannis, D.: Answering top-k queries using views. In: VLDB, pp. 451–462 (2006)
Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci. 66(4), 614–656 (2003)
Gedik, B., Liu, L.: MobiEyes: distributed processing of continuously moving queries on moving objects in a mobile system. In: Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K. (eds.) EDBT 2004. LNCS, vol. 2992, pp. 67–87. Springer, Heidelberg (2004)
Hristidis, V., Koudas, N., Papakonstantinou, Y.: Prefer: a system for the efficient execution of multi-parametric ranked queries. In: SIGMOD Conference, pp. 259–270 (2001)
Hu, H., Xu, J., Lee, D.L.: A generic framework for monitoring continuous spatial queries over moving objects. In: SIGMOD Conference, pp. 479–490 (2005)
Ilyas, I.F., Beskales, G., Soliman, M.A.: A survey of top- query processing techniques in relational database systems. ACM Comput. Surv. 40(4), 1–58 (2008)
Jin, C., Zhang, J., Zhou, A.: Continuous ranking on uncertain streams. Front. Comput. Sci. 6(6), 686–699 (2012)
Mokbel, M.F., Xiong, X., Aref, W.G.: Sina: Scalable incremental processing of continuous queries in spatio-temporal databases. In: SIGMOD Conference, pp. 623–634 (2004)
Mouratidis, K., Bakiras, S., Papadias, D.: Continuous monitoring of top-k queries over sliding windows. In: SIGMOD Conference, pp. 635–646 (2006)
White, W.M., Demers, A.J., Koch, C., Gehrke, J., Rajagopalan, R.: Scaling games to epic proportion. In: SIGMOD Conference, pp. 31–42 (2007)
Wu, W., Guo, W., Tan, K.-L.: Distributed processing of moving k-nearest-neighbor query on moving objects. In: ICDE, pp. 1116–1125 (2007)
Xie, H., Li, Q., Mao, X., Li, X., Cai, Y., Zheng, Q.: Mining latent user community for tag-based and content-based search in social media. Comput. J. 57(9), 1415–1430 (2014)
Xie, M., Lakshmanan, L.V.S., Wood, P.T.: Composite recommendations: from items to packages. Front. Comput. Sci. 6(3), 264–277 (2012)
Yi, K., Yu, H., Yang, J., Xia, G., Chen, Y.: Efficient maintenance of materialized top-k views. In: ICDE, pp. 189–200 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Teng, M., Ma, D., Du, X. (2015). Maintaining Ranking Lists in Dynamic Virtual Environments. In: Liu, A., Ishikawa, Y., Qian, T., Nutanong, S., Cheema, M. (eds) Database Systems for Advanced Applications. DASFAA 2015. Lecture Notes in Computer Science(), vol 9052. Springer, Cham. https://doi.org/10.1007/978-3-319-22324-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-22324-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22323-0
Online ISBN: 978-3-319-22324-7
eBook Packages: Computer ScienceComputer Science (R0)