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dc.contributor.authorLi, Zhixu
dc.contributor.authorSharaf, Mohamed Abdel Fattah
dc.contributor.authorSitbon, Laurianne
dc.contributor.authorSadiq, Shazia Wasim
dc.contributor.authorIndulska, Marta
dc.contributor.authorZhou, Xiaofang
dc.date.accessioned2015-08-24T08:33:33Z
dc.date.available2015-08-24T08:33:33Z
dc.date.issued2013-10-24
dc.identifier.citationLi, Z., Sharaf, M. A., Sitbon, L., Sadiq, S., Indulska, M., & Zhou, X. (2013). A web-based approach to data imputation. World Wide Web, 17(5), 873–897. doi:10.1007/s11280-013-0263-z
dc.identifier.issn1386145X
dc.identifier.doi10.1007/s11280-013-0263-z
dc.identifier.urihttp://hdl.handle.net/10754/575587
dc.description.abstractIn 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.
dc.description.sponsorshipThis research is partially supported by National 863 High-tech Program (Grant No. 2012AA011001) and the Australian Research Council (Grant No. DP110102777).
dc.publisherSpringer Nature
dc.subjectData imputation
dc.subjectIncomplete data
dc.subjectWebPut
dc.titleA web-based approach to data imputation
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalWorld Wide Web
dc.contributor.institutionThe University of QueenslandQueensland, Australia
dc.contributor.institutionThe School of Computer Science and Technology, Soochow UniversityJiangsu, China
dc.contributor.institutionQueensland University of TechnologyQueensland, Australia
kaust.personLi, Zhixu
dc.date.published-online2013-10-24
dc.date.published-print2014-09


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