A web-based approach to data imputation

Zhixu Li, Mohamed Abdel Fattah Sharaf, Laurianne Sitbon, Shazia Wasim Sadiq, Marta Indulska, Xiaofang Zhou

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques. © 2013 Springer Science+Business Media New York.
Original languageEnglish (US)
Pages (from-to)873-897
Number of pages25
JournalWorld Wide Web
Volume17
Issue number5
DOIs
StatePublished - Oct 24 2013

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Computer Networks and Communications

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