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International Conference on Database Systems for Advanced Applications

DASFAA 2017: Database Systems for Advanced Applications pp 527–542Cite as

Drawing Density Core-Sets from Incomplete Relational Data

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10178))

Abstract

Incompleteness is a ubiquitous issue and brings challenges to answer queries with completeness guaranteed. A density core-set is a subset of an incomplete dataset, whose completeness is approximate to the completeness of the entire dataset. Density core-sets are effective mechanisms to estimate completeness of queries on incomplete datasets. This paper studies the problems of drawing density core-sets on incomplete relational data. To the best of our knowledge, there is no such proposal in the past. (1) We study the problems of drawing density core-sets in different requirements, and prove the problems are all NP-Complete whether functional dependencies are given. (2) An efficient approximate algorithm to draw an approximate density core-set is proposed, where an approximate Knapsack algorithm and weighted sampling techniques are employed to select important candidate tuples. (3) Analysis of the proposed approximate algorithm shows the relative error between completeness of the approximate density core-set and that of a density core-set with same size is within a given relative error bound with high probability. (4) Experiments on both real-world and synthetic datasets demonstrate the effectiveness and efficiency of the algorithm.

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Notes

  1. 1.

    DBLP data from http://dblp.uni-trier.de/xml/. Since DBLP is always updating, the data set was downloaded on July 30, 2016.

  2. 2.

    http://www.cars.com.

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Acknowledgments

This work is supported in part by the Key Research and Development Plan of National Ministry of Science and Technology under grant No. 2016YFB1000703, and the Key Program of the National Natural Science Foundation of China under Grant No. 61190115, 61632010 and U1509216.

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Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Yongnan Liu, Jianzhong Li & Hong Gao

Authors
  1. Yongnan Liu
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  2. Jianzhong Li
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  3. Hong Gao
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Corresponding author

Correspondence to Yongnan Liu .

Editor information

Editors and Affiliations

  1. Arizona State University, Tempe - Phoenix, Arizona, USA

    Selçuk Candan

  2. of Science and Technology, Hong Kong University of Science and Technology, Hong Kong, China

    Lei Chen

  3. Aalborg University , Aalborg, Denmark

    Torben Bach Pedersen

  4. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

  5. The University of Queensland , Brisbane, Queensland, Australia

    Wen Hua

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Liu, Y., Li, J., Gao, H. (2017). Drawing Density Core-Sets from Incomplete Relational Data. In: Candan, S., Chen, L., Pedersen, T., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10178. Springer, Cham. https://doi.org/10.1007/978-3-319-55699-4_32

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  • DOI: https://doi.org/10.1007/978-3-319-55699-4_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55698-7

  • Online ISBN: 978-3-319-55699-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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