Professional Network Matters: Connections Empower Person-Job Fit
Authors: 
Hao Chen, Lun Du, Yuxuan Lu, Qiang Fu, Xu Chen, 
Shi Han, Yanbin Kang, Guangming Lu, Zi LiAuthors Info & Claims
Pages 96 - 105
Abstract
Online recruitment platforms typically employ Person-Job Fit models in the core service that automatically match suitable job seekers with appropriate job positions. While existing works leverage historical or contextual information, they often disregard a crucial aspect: job seekers' social relationships in professional networks. This paper emphasizes the importance of incorporating professional networks into the Person-Job Fit model. Our innovative approach consists of two stages: (1) defining a Workplace Heterogeneous Information Network (WHIN) to capture heterogeneous knowledge, including professional connections and pre-training representations of various entities using a heterogeneous graph neural network; (2) designing a Contextual Social Attention Graph Neural Network (CSAGNN) that supplements users' missing information with professional connections' contextual information. We introduce a job-specific attention mechanism in CSAGNN to handle noisy professional networks, leveraging pre-trained entity representations from WHIN. We demonstrate the effectiveness of our approach through experimental evaluations conducted across three real-world recruitment datasets from LinkedIn, showing superior performance compared to baseline models.
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Index Terms
- Professional Network Matters: Connections Empower Person-Job Fit
Recommendations
Modeling Two-Way Selection Preference for Person-Job Fit
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Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning
Research Commentary and Regular PapersPerson-Job Fit is the process of matching the right talent for the right job by identifying talent competencies that are required for the job. While many qualitative efforts have been made in related fields, it still lacks quantitative ways of measuring ...
Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach
SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information RetrievalThe wide spread use of online recruitment services has led to information explosion in the job market. As a result, the recruiters have to seek the intelligent ways for Person-Job Fit, which is the bridge for adapting the right job seekers to the right ...
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March 2024
1246 pages
ISBN:9798400703713
DOI:10.1145/3616855
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Published: 04 March 2024
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