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Frontiers of Computer Science

Front. Comput. Sci.    2018, Vol. 12 Issue (1) : 4-25     https://doi.org/10.1007/s11704-016-6195-x
REVIEW ARTICLE |
Incomplete data management: a survey
Xiaoye MIAO1, Yunjun GAO1,2(), Su GUO1, Wanqi LIU1
1. College of Computer Science, Zhejiang University, Hangzhou 310027, China
2. The Key Lab of Big Data Intelligent Computing of Zhejiang Province, Zhejiang University, Hangzhou 310027, China
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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     
Corresponding Authors: Yunjun GAO   
Just Accepted Date: 28 September 2016   Online First Date: 17 March 2017    Issue Date: 12 January 2018
 Cite this article:   
Xiaoye MIAO,Yunjun GAO,Su GUO, et al. Incomplete data management: a survey[J]. Front. Comput. Sci., 2018, 12(1): 4-25.
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http://journal.hep.com.cn/fcs/EN/10.1007/s11704-016-6195-x
http://journal.hep.com.cn/fcs/EN/Y2018/V12/I1/4
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Xiaoye MIAO
Yunjun GAO
Su GUO
Wanqi LIU
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