Lessons Learned from Developing and Deploying a Large-Scale Employer Name Normalization System for Online Recruitment

被引:2
|
作者
Liu, Qiaoling [1 ]
Chao, Josh [1 ]
Mahoney, Thomas [1 ]
Chern, Alan [1 ]
Min, Chris [1 ]
Javed, Faizan [1 ]
Jijkoun, Valentin [2 ]
机构
[1] CareerBuilder LLC, Norcross, GA 30092 USA
[2] Textkernel BV, Amsterdam, Netherlands
关键词
D O I
10.1145/3219819.3219842
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Employer name normalization, or linking employer names in job postings or resumes to entities in an employer knowledge base (KB), is important for many downstream applications in the online recruitment domain. Key challenges for employer name normalization include handling employer names from both job postings and resumes, leveraging the corresponding location and URL context, and handling name variations and duplicates in the KB. In this paper, we describe the CompanyDepot system developed at CareerBuilder, which uses machine learning techniques to address these challenges. We discuss the main challenges and share our lessons learned in deployment, maintenance, and utilization of the system over the past two years. We also share several examples of how the system has been used in applications at CareerBuilder to deliver value to end customers.
引用
收藏
页码:556 / 565
页数:10
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