期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 122, 期 -, 页码 16-26出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2018.12.038
关键词
Granular computing; Three-way decision; Uncertain region; Record linkage
类别
资金
- Natural Sciences and Engineering Research Council of Canada (NSERC) [STPGP 462980]
Record linkage is a typical two-class recognition problem in data mining. To improve its classification performance of the problem, this paper proposes to apply three-way classification to identify uncertain points (regions) for further clerical investigation in decision-making. The detailed three-way decision process is realized by a two-phase approach. During the first phase, an information granule is constructed to describe the uncertain region in the data space. In the second phase, the constructed granule is utilized to discriminate between certain points (those with a high likelihood of belonging to one of the classes) and uncertain points (viz. those requiring clerical attention). For uncertain points, manual investigation is realized; for certain points, the generic binary classifier is applied for classification. Synthetic data and publicly available data are used to demonstrate the performance of the proposed approach. Finally, the proposed approach is shown effective in applications involving real-world record linkage data. (C) 2018 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据