Abstract
Given a set of objects and a query q, a point p is q’s reverse k nearest neighbour (R\(k\)NN) if q is one of p’s k-closest objects. R\(k\)NN queries have received significant research attention in the past few years. However, we realise that the state-of-the-art algorithm, SLICE, accesses many objects that do not contribute to its \({\text {R}kNN} \) results when running the filtering phase, which deteriorates the query performance. In this paper, we propose a novel R\(k\)NN algorithm with pre-computation by partitioning the data space into disjoint rectangular regions and constructing the guardian set for each region R. We guarantee that, for each q that lies in R, its R\(k'\)NN results are only affected by the objects in R’s guardian set, where \(k' \le k\). The advantage of this approach is that the results of a query \(q\in R\) can be computed by using SLICE on only the objects in its guardian set instead of using the whole dataset. Our comprehensive experimental study on synthetic and real datasets demonstrates the proposed approach is the most efficient algorithm for R\(k\)NN.
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Cheema, M.A., Lin, X., Zhang, W., Zhang, Y.: Influence zone: efficiently processing reverse k nearest neighbors queries. In: 27th International Conference on Data Engineering (ICDE), pp. 577–588. IEEE (2011)
Wu, W., Yang, F., Chan, C.Y., Tan, K.L.: Finch: evaluating reverse k-nearest-neighbor queries on location data. Proc. VLDB Endow. 1(1), 1056–1067 (2008)
Yang, S., Cheema, M.A., Lin, X., Zhang, Y.: Slice: reviving regions-based pruning for reverse k nearest neighbors queries. In: 30th International Conference on Data Engineering (ICDE), pp. 760–771. IEEE (2014)
Tao, Y., Papadias, D., Lian, X.: Reverse kNN search in arbitrary dimensionality. In: Proceedings of the Thirtieth International Conference on Very Large Data Bases. vol. 30, pp. 744–755. VLDB Endowment (2004)
Stanoi, I., Agrawal, D., El Abbadi, A.: Reverse nearest neighbor queries for dynamic databases. In: ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp. 44–53 (2000)
Güting, R.H.: An introduction to spatial database systems. Int. J. Very Large Data Bases 3(4), 357–399 (1994)
Korn, F., Muthukrishnan, S.: Influence sets based on reverse nearest neighbor queries. ACM SIGMOD Rec. 29(2), 201–212 (2000). ACM
Yang, C., Lin, K.I.: An index structure for efficient reverse nearest neighbour queries. In: 17th International Conference on Data Engineering Proceedings, pp. 485–492. IEEE (2001)
Tao, Y., Papadias, D., Lian, X., Xiao, X.: Multidimensional reverse kNN search. VLDB J. 16(3), 293–316 (2007)
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)
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)
Cheema, M.A., Brankovic, L., Lin, X., Zhang, W., Wang, W.: Multi-guarded safe zone: an effective technique to monitor moving circular range queries. In: IEEE 26th International Conference on Data Engineering (ICDE), pp. 189–200. IEEE (2010)
Cheema, M.A., Zhang, W., Lin, X., Zhang, Y.: Efficiently processing snapshot and continuous reverse k nearest neighbors queries. VLDB J. 21(5), 703–728 (2012)
Yang, S., Cheema, M.A., Lin, X., Wang, W.: Reverse k nearest neighbors query processing: experiments and analysis. Proc. VLDB Endow. 8(5), 605–616 (2015)
Ruemmler, C., Wilkes, J.: UNIX disk access patterns. In: USENIX Winter, vol. 93, pp. 405–420 (1993)
Tsirogiannis, D., Harizopoulos, S., Shah, M.A., Wiener, J.L., Graefe, G.: Query processing techniques for solid state drives. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pp. 59–72. ACM (2009)
Acknowledgements
Research of Wei Wang is supported by ARC DP130103401 and DP130103405. Muhammad Aamir Cheema is supported by ARC DE130101002 and DP130103405.
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Song, W., Qin, J., Wang, W., Cheema, M.A. (2016). Pre-computed Region Guardian Sets Based Reverse kNN Queries. In: Navathe, S., Wu, W., Shekhar, S., Du, X., Wang, S., Xiong, H. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9643. Springer, Cham. https://doi.org/10.1007/978-3-319-32049-6_7
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DOI: https://doi.org/10.1007/978-3-319-32049-6_7
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