A web-based approach to data imputation

Handle URI:
http://hdl.handle.net/10754/575587
Title:
A web-based approach to data imputation
Authors:
Li, Zhixu; Sharaf, Mohamed Abdel Fattah; Sitbon, Laurianne; Sadiq, Shazia Wasim; Indulska, Marta; Zhou, Xiaofang
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Springer Science + Business Media
Journal:
World Wide Web
Issue Date:
24-Oct-2013
DOI:
10.1007/s11280-013-0263-z
Type:
Article
ISSN:
1386145X
Sponsors:
This research is partially supported by National 863 High-tech Program (Grant No. 2012AA011001) and the Australian Research Council (Grant No. DP110102777).
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Zhixuen
dc.contributor.authorSharaf, Mohamed Abdel Fattahen
dc.contributor.authorSitbon, Laurianneen
dc.contributor.authorSadiq, Shazia Wasimen
dc.contributor.authorIndulska, Martaen
dc.contributor.authorZhou, Xiaofangen
dc.date.accessioned2015-08-24T08:33:33Zen
dc.date.available2015-08-24T08:33:33Zen
dc.date.issued2013-10-24en
dc.identifier.issn1386145Xen
dc.identifier.doi10.1007/s11280-013-0263-zen
dc.identifier.urihttp://hdl.handle.net/10754/575587en
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.en
dc.description.sponsorshipThis research is partially supported by National 863 High-tech Program (Grant No. 2012AA011001) and the Australian Research Council (Grant No. DP110102777).en
dc.publisherSpringer Science + Business Mediaen
dc.subjectData imputationen
dc.subjectIncomplete dataen
dc.subjectWebPuten
dc.titleA web-based approach to data imputationen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalWorld Wide Weben
dc.contributor.institutionThe University of QueenslandQueensland, Australiaen
dc.contributor.institutionThe School of Computer Science and Technology, Soochow UniversityJiangsu, Chinaen
dc.contributor.institutionQueensland University of TechnologyQueensland, Australiaen
kaust.authorLi, Zhixuen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.