WebPut: A web-aided data imputation system for the general type of missing string attribute values

Shuangli Shan; Zhixu Li; Yang Li; Qiang Yang; Jia Zhu; Mohamed Sharaf; Xiaofang Zhou

doi:10.1109/ICDE.2019.00212

WebPut: A web-aided data imputation system for the general type of missing string attribute values

Shuangli Shan, Zhixu Li, Yang Li, Qiang Yang, Jia Zhu, Mohamed Sharaf, Xiaofang Zhou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
Publisher	IEEE Computer Society
Pages	1952-1955
Number of pages	4
ISBN (Electronic)	9781538674741
DOIs	https://doi.org/10.1109/ICDE.2019.00212
Publication status	Published - Apr 2019
Externally published	Yes
Event	35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China Duration: Apr 8 2019 → Apr 11 2019

Publication series

Name	Proceedings - International Conference on Data Engineering
Volume	2019-April
ISSN (Print)	1084-4627

Conference

Conference	35th IEEE International Conference on Data Engineering, ICDE 2019
Country/Territory	China
City	Macau
Period	4/8/19 → 4/11/19

Keywords

Data imputation
Incomplete data
Webput

ASJC Scopus subject areas

Software
Signal Processing
Information Systems

Access to Document

10.1109/ICDE.2019.00212

Cite this

Shan, S., Li, Z., Li, Y., Yang, Q., Zhu, J., Sharaf, M., & Zhou, X. (2019). WebPut: A web-aided data imputation system for the general type of missing string attribute values. In Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019 (pp. 1952-1955). Article 8731367 (Proceedings - International Conference on Data Engineering; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ICDE.2019.00212

WebPut: A web-aided data imputation system for the general type of missing string attribute values. / Shan, Shuangli; Li, Zhixu; Li, Yang et al.
Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019. IEEE Computer Society, 2019. p. 1952-1955 8731367 (Proceedings - International Conference on Data Engineering; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shan, S, Li, Z, Li, Y, Yang, Q, Zhu, J, Sharaf, M & Zhou, X 2019, WebPut: A web-aided data imputation system for the general type of missing string attribute values. in Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019., 8731367, Proceedings - International Conference on Data Engineering, vol. 2019-April, IEEE Computer Society, pp. 1952-1955, 35th IEEE International Conference on Data Engineering, ICDE 2019, Macau, China, 4/8/19. https://doi.org/10.1109/ICDE.2019.00212

Shan S, Li Z, Li Y, Yang Q, Zhu J, Sharaf M et al. WebPut: A web-aided data imputation system for the general type of missing string attribute values. In Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019. IEEE Computer Society. 2019. p. 1952-1955. 8731367. (Proceedings - International Conference on Data Engineering). doi: 10.1109/ICDE.2019.00212

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WebPut: A web-aided data imputation system for the general type of missing string attribute values

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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