TY - GEN
T1 - WebPut
T2 - 13th International Conference on Web Information Systems Engineering, WISE 2012
AU - Li, Zhixu
AU - Sharaf, Mohamed A.
AU - Sitbon, Laurianne
AU - Sadiq, Shazia
AU - Indulska, Marta
AU - Zhou, Xiaofang
PY - 2012
Y1 - 2012
N2 - 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 also 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. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.
AB - 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 also 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. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.
KW - Incomplete Data
KW - Web-based Data Imputation
KW - WebPut
UR - http://www.scopus.com/inward/record.url?scp=84869477380&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869477380&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35063-4_18
DO - 10.1007/978-3-642-35063-4_18
M3 - Conference contribution
AN - SCOPUS:84869477380
SN - 9783642350627
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 256
BT - Web Information Systems Engineering, WISE 2012 - 13th International Conference, Proceedings
Y2 - 28 November 2012 through 30 November 2012
ER -