Improved Top-k Query Processing on Uncertain Data

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Abstract:

Bottom-up algorithm, which is one of the two probabilistic Top-k query algorithms, was improved. The core of the bottomup algorithm is the iteration on the three courses of bounding, pruning,and refining towards the objects and instances. The main contribution is to change the iteration on instances of objects one by one into iterating all the instances of objects from the superior to the inferior;and to transform the condition and sequence of pruning in order to make the pruning more effective. Theoretical analysis and experimental results show that the algorithm efficiency could be obviously increased by about 20%.

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2837-2840

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Alon Halevy, Michael Franklin, Principle of Dataspace Systems, 2006, dl. acm. org.

Google Scholar

[2] Zhou Fan, Li Shuquan, Top-k query processing on probabilistic data, Journal Of Electronic Measurement And Instrument, 2007, Vol. 24 No. 7 605~656.

Google Scholar

[3] Michael Franklin, Alon Halevy, From Database to Dataspaces: A New Abstraction For Information Management, 2005. 12, ACM SIGMOD.

DOI: 10.1145/1107499.1107502

Google Scholar

[4] X. Dong, A, Halevy and C. Yu. Probabilistic schema mapping. Technical Report 2006-12-01, Univ. of Washington, (2006).

Google Scholar

[5] X. Dong, A, Halevy. A platform for personal information management and integration. In CIDR, (2005).

Google Scholar

[6] Ao-Ying Zhou, Che-Qing Jin, A Survey on the Management of Uncertain Data, Chinese Journal of Computers, 2009, Vol. 32 No. 1.

Google Scholar

[7] Li Jian-Zhong, Li Jin-Bao, Concepts, issues and advance of sensor networks and data management of sensor networks. Journal of software, 2003, 14(10): 1717-1727.

Google Scholar

[8] L. A. Adamic and E. Adar. How to search a social network. Social Networks, 27(3): 187{203, (2005).

DOI: 10.1016/j.socnet.2005.01.007

Google Scholar

[9] E. Adar and C. Re. Managing uncertainty in social networks. IEEE Data Engineering Bulletin, 30(2): 15{22, (2007).

Google Scholar

[10] R. Ananthakrishna, S. Chaudhuri, and V. Ganti. Eliminating fuzzy duplicates in data warehouses. In VLDB, (2002).

DOI: 10.1016/b978-155860869-6/50058-5

Google Scholar