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    Web-ADARE: A Web-Aided Data Repairing System

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    1-s2.0-S0925231217304642-main.pdf
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    Description:
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    Type
    Article
    Authors
    Gu, Binbin
    Li, Zhixu
    Yang, Qiang
    Xie, Qing cc
    Liu, An
    Liu, Guanfeng
    Zheng, Kai
    Zhang, Xiangliang cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Date
    2017-03-08
    Online Publication Date
    2017-03-08
    Print Publication Date
    2017-08
    Permanent link to this record
    http://hdl.handle.net/10754/623010
    
    Metadata
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    Abstract
    Data repairing aims at discovering and correcting erroneous data in databases. In this paper, we develop Web-ADARE, an end-to-end web-aided data repairing system, to provide a feasible way to involve the vast data sources on the Web in data repairing. Our main attention in developing Web-ADARE is paid on the interaction problem between web-aided repairing and rule-based repairing, in order to minimize the Web consultation cost while reaching predefined quality requirements. The same interaction problem also exists in crowd-based methods but this is not yet formally defined and addressed. We first prove in theory that the optimal interaction scheme is not feasible to be achieved, and then propose an algorithm to identify a scheme for efficient interaction by investigating the inconsistencies and the dependencies between values in the repairing process. Extensive experiments on three data collections demonstrate the high repairing precision and recall of Web-ADARE, and the efficiency of the generated interaction scheme over several baseline ones.
    Citation
    Gu B, Li Z, Yang Q, Xie Q, Liu A, et al. (2017) Web-ADARE: A Web-Aided Data Repairing System. Neurocomputing. Available: http://dx.doi.org/10.1016/j.neucom.2016.09.132.
    Sponsors
    This research is partially supported by Natural Science Foundation of China (Grant No. 61303019, 61402313, 61472263, 61572336), Postdoctoral scientific research funding of Jiangsu Province (No. 1501090B) National 58 batch of postdoctoral funding (No. 2015M581859), Collaborative Innovation Center of Novel Software Technology and Industrialization, Jiangsu, China, and the King Abdullah University of Science and Technology.
    Publisher
    Elsevier BV
    Journal
    Neurocomputing
    DOI
    10.1016/j.neucom.2016.09.132
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0925231217304642
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.neucom.2016.09.132
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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