preprint Open access

Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned

  • arXiv (Cornell University)
  • Cornell University
Research footprint

At a glance

Citations
1
References
4
Comments
0
Paper overview

Abstract

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.

Record transparency

Publication details

DOI
10.48550/arxiv.1809.06481
OpenAlex
W2951477660
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
Last metadata update
Community

Comments

Log in to join the discussion.

  1. No comments yet. Start the discussion.