Abstract
An important topic in the field of spatial data management is processing the queries involving uncertain locations. This paper focuses on the problem of finding probabilistic K closest pairs between two uncertain spatial datasets, namely, Top-K probabilistic closest pairs (TopK-PCP) query, which has popular usages in real applications. Specifically, given two uncertain datasets in which each spatial object is modeled by a set of sample points, a TopK-PCP query retrieves the pairs with top K maximal probabilities of being the closest pair. Due to the inherent uncertainty of data objects, previous techniques to answer K-closest pairs (K-CP) queries cannot be directly applied to our TopK-PCP problem. Motivated by this, we propose a novel method to evaluate TopK-PCP query effectively. Extensive experiments are performed to demonstrate the effectiveness of our method.
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References
Corral, A., Manolopoulos, Y., Theodoridis, Y., Vassilakopoulos, M.: Closest pair queries in spatial databases. In: SIGMOD, pp. 189–200 (2000)
Zhu, M., Lee, D.L., Zhang, J.: k-closest pair query monitoring over moving objects. In: MDM, vol. 14 (2006)
Hjaltason, G.R., Samet, H.: Incremental distance join algorithms for spatial databases. In: SIGMOD, pp. 237–248 (1998)
Corral, A., Manolopoulos, Y., Theodoridis, Y., Vassilakopoulos, M.: Algorithms for processing k-closest-pair queries in spatial databases. Data and Knowledge Engineering 49, 67–104 (2004)
Yang, C., Lin, K.I.: An index structure for improving nearest closest pairs and related join queries in spatial databases. In: IDEAS, pp. 140–149 (2002)
Leong Hou, U., Mamoulis, N., Yiu, M.L.: Computation and monitoring of exclusive closest pairs. IEEE Trans. Knowl. Data Eng (TKDE) 20(12), 1641–1654 (2008)
Aggarwal, C.C., Yu, P.S.: A survey of uncertain data algorithms and applications. IEEE Trans. Knowl. Data Eng (TKDE) 21(5), 609–623 (2009)
Singh, S., Mayfield, C., Shah, R., Prabhakar, S., Hambrusch, S.E., Neville, J., Cheng, R.: Database support for probabilistic attributes and tuples. In: ICDE, pp. 1053–1061 (2008)
Bosc, P., Pivert, O.: Modeling and querying uncertain relational databases: a survey of approaches based on the possible worlds semantics. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) 18(5), 565–603 (2010)
Dalvi, N.N., Suciu, D.: Efficient query evaluation on probabilistic databases. VLDB J. 16(4), 523–544 (2007)
Chang, L., Yu, J.X., Qin, L.: Query ranking in probabilistic xml data. In: EDBT, pp. 156–167 (2009)
Xu, J., Zhang, Z., Tung, A.K.H., Yu, G.: Efficient and effective similarity search over probabilistic data based on earth mover’s distance. PVLDB 3(1), 758–769 (2010)
Cheng, R., Kalashnikov, D.V., Prabhakar, S.: Evaluating probabilistic queries over imprecise data. In: SIGMOD, pp. 551–562 (2003)
Xu, C., Wang, Y., Lin, S., Gu, Y., Qiao, J.: Efficient fuzzy top-k query processing over uncertain objects. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds.) DEXA 2010. LNCS, vol. 6261, pp. 167–182. Springer, Heidelberg (2010)
Pei, J., Jiang, B., Lin, X., Yuan, Y.: Probabilistic skylines on uncertain data. In: VLDB, pp. 15–26 (2007)
Kriegel, H.-P., Kunath, P., Renz, M.: Probabilistic nearest-neighbor query on uncertain objects. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 337–348. Springer, Heidelberg (2007)
Yang, S., Zhang, W., Zhang, Y., Lin, X.: Probabilistic threshold range aggregate query processing over uncertain data. In: APWeb/WAIM, pp. 51–62 (2009)
Beskales, G., Soliman, M.A., Ilyas, I.F.: Efficient search for the top-k probable nearest neighbors in uncertain databases. PVLDB 1(1), 326–339 (2008)
Lian, X., Chen, L.: Efficient processing of probabilistic reverse nearest neighbor queries over uncertain data. VLDB J. 18(3), 787–808 (2009)
Soliman, M.A., Ilyas, I.F., Chang, K.C.-C.: Top-k query processing in uncertain databases. In: ICDE, pp. 896–905 (2007)
Jin, C., Yi, K., Chen, L., Yu, J.X., Lin, X.: Sliding-window top-k queries on uncertain streams. PVLDB 1(1), 301–312 (2008)
Lian, X., Chen, L.: Probabilistic group nearest neighbor queries in uncertain databases. IEEE Trans. Knowl. Data Eng (TKDE) 20(6), 809–824 (2008)
Kriegel, H.-P., Kunath, P., Pfeifle, M., Renz, M.: Probabilistic similarity join on uncertain data. In: Li Lee, M., Tan, K.-L., Wuwongse, V. (eds.) DASFAA 2006. LNCS, vol. 3882, pp. 295–309. Springer, Heidelberg (2006)
Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The r*-tree: An efficient and robust access method for points and rectangles. In: SIGMOD, pp. 322–331 (1990)
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Chen, M., Jia, Z., Gu, Y., Yu, G. (2011). Top-K Probabilistic Closest Pairs Query in Uncertain Spatial Databases. In: Du, X., Fan, W., Wang, J., Peng, Z., Sharaf, M.A. (eds) Web Technologies and Applications. APWeb 2011. Lecture Notes in Computer Science, vol 6612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20291-9_8
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DOI: https://doi.org/10.1007/978-3-642-20291-9_8
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