Improving Machine-based Entity Resolution with Limited Human Effort-Reference-Cited by-同舟云学术

Improving Machine-based Entity Resolution with Limited Human Effort

Published:2018-08-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics
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Author:

Chen Zhaoqiang¹,Chen Qun¹,Hou Boyi¹,Ahmed Murtadha¹,Li Zhanhuai¹

Affiliation:

1. School of Computer Science, Northwestern Polytechnical University, China and Key Laboratory of Big Data Storage and Management, NPU, MIIT, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3242153.3242156

Reference13 articles.

1. James O Berger . 1985. Statistical decision theory and Bayesian analysis . Springer Series in Statistics New York : Springer 2 nd ed. James O Berger. 1985. Statistical decision theory and Bayesian analysis. Springer Series in Statistics New York: Springer 2nd ed.

2. John Burkardt. 2014. The truncated normal distribution. Department of Scientific Computing Website Florida State University (2014). John Burkardt. 2014. The truncated normal distribution. Department of Scientific Computing Website Florida State University (2014).

3. Cost-Effective Crowdsourced Entity Resolution

4. Zhaoqiang Chen Qun Chen etal 2018. Improving the Results of Machine-based Entity Resolution with Limited Human Effort: A Risk Perspective. Technical Report. http://www.wowbigdata.com.cn/risker18report.pdf Zhaoqiang Chen Qun Chen et al. 2018. Improving the Results of Machine-based Entity Resolution with Limited Human Effort: A Risk Perspective. Technical Report. http://www.wowbigdata.com.cn/risker18report.pdf

5. Data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection. Springer Science & Business Media;Christen Peter;Chapter,2012

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