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Cost Reduction for Web-Based Data Imputation

  • Zhixu Li
  • Shuo Shang
  • Qing Xie
  • Xiangliang Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8422)

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.

Keywords

Web-based Data Imputation Imputation Query Cost Reduction 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Zhixu Li
    • 1
  • Shuo Shang
    • 2
  • Qing Xie
    • 1
  • Xiangliang Zhang
    • 1
  1. 1.King Abdullah University of Science and TechnologySaudi Arabia
  2. 2.Department of Software EngineeringChina University of Petroleum-BeijingP.R. China

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