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Frontiers of Computer Science

, Volume 13, Issue 1, pp 215–217 | Cite as

Statistical relational learning based automatic data cleaning

  • Weibang LiEmail author
  • Ling Li
  • Zhanhuai Li
  • Mengtian Cui
Letter
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Notes

Acknowledgements

The work was supported by the Fundamental Research Funds for the Central Universities, Southwest Minzu University (2018NQN32), the National High Technology Research and Development Program 863 of China (2015AA015307), the National Natural Science Foundation of China (Grant Nos. 61672432, 61702161), the Key Research and Development and Promotion Program of Henan Province of China (182102210213), and the Foundation of Henan Educational Committee (18A520003).

Supplementary material

11704_2018_7066_MOESM1_ESM.pdf (330 kb)
Statistical relational learning based automatic data cleaning

References

  1. 1.
    Carlo B, Monica S. Data Quality: Concepts, Methodologies and Techniques. Berlin: Springer Publishing Company, 2006zbMATHGoogle Scholar
  2. 2.
    Doshi P, Greenwald L, Clarke J R. Using Bayesian networks for cleansing trauma data. In: Proceedings of the 6th International Florida Artificial Intelligence Research Society Conference. 2003, 72–76Google Scholar
  3. 3.
    Yakout M, Elmagarmid A K, Neville J, Ouzzani M, Ilyas I F. Guided data repair. Proceedings of the VLDB Endowment, 2011, 4(5): 279–289CrossRefGoogle Scholar
  4. 4.
    Wang J, Kraska T, Franklin M J, Feng J. Crowder: crowdsourcing entity resolution. Proceedings of the VLDB Endowment, 2012, 5(11): 1483–1494CrossRefGoogle Scholar
  5. 5.
    Fan W, Geerts F, Jia X, Kementsietsidis A. Conditional functional dependencies for capturing data inconsistencies. Journal of ACM Transactions on Database Systems, 2008, 33(2): 1–48CrossRefGoogle Scholar
  6. 6.
    Smyth P, Goodman R M. Rule induction using information theory. In: Proceedings of the International Conference on Knowledge Discovery in Databases. 1991, 159–176Google Scholar
  7. 7.
    Hu Y, De S, Chen Y, Kambhampati S. Bayesian data cleaning for Web data. 2012, arXiv preprint arXiv:1204.3677Google Scholar
  8. 8.
    De S, Hu Y, Meduri V, Chen Y, Kambhampati S. Bayeswipe: a scalable probabilistic framework for improving data quality. Journal of Data and Information Quality, 2016, 8(1): 1–30CrossRefGoogle Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Weibang Li
    • 1
    Email author
  • Ling Li
    • 2
  • Zhanhuai Li
    • 3
  • Mengtian Cui
    • 1
  1. 1.School of Computer Science and TechnologySouthwest Minzu UniversityChengduChina
  2. 2.Archives of Southwest Minzu UniversityChengduChina
  3. 3.College of Computer ScienceNorthwestern Polytechnical UniversityXi’anChina

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