Paper Info
Title
Leveraging Currency for Repairing Inconsistent and Incomplete Data
Abstract
Data quality plays a key role in big data management today. With the explosive growth of data from a variety of sources, the quality of data is faced with multiple problems. Motivated by this, we study the multiple data cleaning on incompleteness and inconsistency with currency reasoning and determination in this paper. We introduce a 4-step framework, named <inline-formula><tex-math notation="LaTeX">${\sf Imp3C}$</tex-math></inline-formula> , for errors detection and quality improvement in incomplete and inconsistent data without timestamps. We achieve an integrated currency determining method to compute the currency orders among tuples, according to currency constraints. Thus, the inconsistent data and missing values are repaired effectively considering the temporal impact. For both effectiveness and efficiency consideration, we carry out inconsistency repair ahead of incompleteness repair. A currency-related consistency distance metric is defined to measure the similarity between dirty tuples and clean ones more accurately. In addition, currency orders are treated as an important feature in the missing imputation training process. The solution algorithms are introduced in detail with case studies. A thorough experiment on three real-life datasets verifies our method <inline-formula><tex-math notation="LaTeX">${\sf Imp3C}$</tex-math></inline-formula> improves the performance of data repairing with multiple quality problems. <inline-formula><tex-math notation="LaTeX">${\sf Imp3C}$</tex-math></inline-formula> outperforms the existing advanced methods, especially in the datasets with complex currency orders.
Year
DOI
Venue
2022
10.1109/TKDE.2020.2992456
IEEE Transactions on Knowledge and Data Engineering
Keywords
DocType
Volume
Data cleaning,data quality management,currency determining,temporal data repairing
Journal
34
Issue
ISSN
Citations 
3
1041-4347
1
PageRank 
References 
Authors
0.35
0
6
Name
Order
Citations
PageRank
Xiaoou Ding122.38
Hongzhi Wang242173.72
Jiaxuan Su322.05
Muxian Wang410.35
Jianzhong Li53196304.46
Hong Gao61086120.07