Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned
This work tackles real-world problems in a large-scale professional networking platform, but it is incremental as it focuses on lessons learned rather than introducing new methods.
The paper addresses the practical challenges in developing LinkedIn's talent search and recommendation systems, which are crucial for matching job seekers with job providers, though it does not report specific numerical results.
LinkedIn Talent Solutions business contributes to around 65% of LinkedIn's annual revenue, and provides tools for job providers to reach out to potential candidates and for job seekers to find suitable career opportunities. LinkedIn's job ecosystem has been designed as a platform to connect job providers and job seekers, and to serve as a marketplace for efficient matching between potential candidates and job openings. A key mechanism to help achieve these goals is the LinkedIn Recruiter product, which enables recruiters to search for relevant candidates and obtain candidate recommendations for their job postings. In this work, we highlight a set of unique information retrieval, system, and modeling challenges associated with talent search and recommendation systems.