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Frontiers of Computer Science

, Volume 12, Issue 1, pp 4–25 | Cite as

Incomplete data management: a survey

  • Xiaoye Miao
  • Yunjun Gao
  • Su Guo
  • Wanqi Liu
Review Article

Abstract

Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query incomplete data incurs big challenges. For example, the queries struggling with incomplete data usually have dissatisfying query results due to the improper incompleteness handling methods. In this paper, we systematically review the management of incomplete data, including modelling, indexing, querying, and handling methods in terms of incomplete data. We also overview several application scenarios of incomplete data, and summarize the existing systems related to incomplete data. It is our hope that this survey could provide insights to the database community on how incomplete data is managed, and inspire database researchers to develop more advanced processing techniques and tools to cope with the issues resulting from incomplete data in the real world.

Keywords

incomplete data query processing indexing application system 

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Notes

Acknowledgements

This work was supported in part by the National Key Basic Research Program of China (973 Program) (2015CB352502), the National Natural Science Foundation of China (NSFC) (Grant Nos. 61522208, 61379033, and 61472348), and the Fundamental Research Funds for the Central Universities.

Supplementary material

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Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2018

Authors and Affiliations

  1. 1.College of Computer ScienceZhejiang UniversityHangzhouChina
  2. 2.The Key Lab of Big Data Intelligent Computing of Zhejiang ProvinceZhejiang UniversityHangzhouChina

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