Conference
PARC
Abstract
Poor data quality has become a persistent challenge for organizations as data continues to grow in complexity and size. Existing data cleaning solutions focus on identifying repairs to the data to minimize either a cost function or the number of updates. These techniques, however, fail to consider underlying data privacy requirements that exist in many real data sets containing sensitive and personal information. In this demonstration, we …
Authors
Huang D; Gairola D; Huang Y; Zheng Z; Chiang F
Pagination
pp. 2433-2436
Publisher
Association for Computing Machinery (ACM)
Publication Date
October 24, 2016
DOI
10.1145/2983323.2983326
Name of conference
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management