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    Cost reduction for web-based data imputation

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    Type
    Conference Paper
    Authors
    Li, Zhixu
    Shang, Shuo
    Xie, Qing cc
    Zhang, Xiangliang cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Machine Intelligence & kNowledge Engineering Lab
    Date
    2014-04-16
    Online Publication Date
    2014-04-16
    Print Publication Date
    2014
    Permanent link to this record
    http://hdl.handle.net/10754/564875
    
    Metadata
    Show full item record
    Abstract
    Web-based Data Imputation enables the completion of incomplete data sets by retrieving absent field values from the Web. In particular, complete fields can be used as keywords in imputation queries for absent fields. However, due to the ambiguity of these keywords and the data complexity on the Web, different queries may retrieve different answers to the same absent field value. To decide the most probable right answer to each absent filed value, existing method issues quite a few available imputation queries for each absent value, and then vote on deciding the most probable right answer. As a result, we have to issue a large number of imputation queries for filling all absent values in an incomplete data set, which brings a large overhead. In this paper, we work on reducing the cost of Web-based Data Imputation in two aspects: First, we propose a query execution scheme which can secure the most probable right answer to an absent field value by issuing as few imputation queries as possible. Second, we recognize and prune queries that probably will fail to return any answers a priori. Our extensive experimental evaluation shows that our proposed techniques substantially reduce the cost of Web-based Imputation without hurting its high imputation accuracy. © 2014 Springer International Publishing Switzerland.
    Citation
    Li, Z., Shang, S., Xie, Q., & Zhang, X. (2014). Cost Reduction for Web-Based Data Imputation. Lecture Notes in Computer Science, 438–452. doi:10.1007/978-3-319-05813-9_29
    Publisher
    Springer Nature
    Journal
    Database Systems for Advanced Applications
    Conference/Event name
    19th International Conference on Database Systems for Advanced Applications, DASFAA 2014
    ISBN
    9783319058122
    DOI
    10.1007/978-3-319-05813-9_29
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-319-05813-9_29
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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