TY - GEN
T1 - WebPut
T2 - 35th IEEE International Conference on Data Engineering, ICDE 2019
AU - Shan, Shuangli
AU - Li, Zhixu
AU - Li, Yang
AU - Yang, Qiang
AU - Zhu, Jia
AU - Sharaf, Mohamed
AU - Zhou, Xiaofang
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.
AB - In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.
KW - Data imputation
KW - Incomplete data
KW - Webput
UR - http://www.scopus.com/inward/record.url?scp=85067940433&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067940433&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2019.00212
DO - 10.1109/ICDE.2019.00212
M3 - Conference contribution
AN - SCOPUS:85067940433
T3 - Proceedings - International Conference on Data Engineering
SP - 1952
EP - 1955
BT - Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PB - IEEE Computer Society
Y2 - 8 April 2019 through 11 April 2019
ER -