Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach

Abstract

To cope with the accelerating pace of technological changes, talents are urged to add and refresh their skills for staying in active and gainful employment. This raises a natural question: what are the right skills to learn? Indeed, it is a nontrivial task to measure the popularity of job skills due to the diversified criteria of jobs and the complicated connections within job skills. To that end, in this paper, we propose a data driven approach for modeling the popularity of job skills based on the analysis of large-scale recruitment data. Specifically, we first build a job skill network by exploring a large corpus of job postings. Then, we develop a novel Skill Popularity based Topic Model (SPTM) for modeling the generation of the skill network. In particular, SPTM can integrate different criteria of jobs (e.g., salary levels, company size) as well as the latent connections within skills, thus we can effectively rank the job skills based on their multi-faceted popularity. Extensive experiments on real-world recruitment data validate the effectiveness of SPTM for measuring the popularity of job skills, and also reveal some interesting rules, such as the popular job skills which lead to high-paid employment.

Person-job fit estimation from candidate profile and related recruitment history with co-attention neural networks

“…[12] [17] analyze the differences in job requirements between technical recruitment and non-technical recruitment. [37] propose a data-driven approach for modeling the popularity of job skills based on the analysis of large-scale recruitment data.…”

“…Due to its high practical value, Person-job fit has received increasing research interest [37,24,29,41,27]. Among these researches, a typical approach is to convert the task to a supervised text matching problem, which aims at calculating the matching degree based on the text content of job postings and resumes.…”

Modeling Two-Way Selection Preference for Person-Job Fit

“…In the literature, a variety of studies have been conducted for person-job fit, such as reciprocal recommendation [23], job recommendation [18,29,48] and job-oriented skill measurement [43]. Since the information of job and candidate is usually organized and described in textual documents, many text-based person-job fit works have been proposed in recent years, which learn matching function by modeling the textual semantics [31,55].…”

Skills2Job: A Recommender System that Encodes Job Offer Embeddings on Graph Databases (Student Abstract)

“…Given the very high number of job positions and applicants on online job portals, the problem of person-job fit has become relevant in recent literature, both as a skill measuring system (Xu et al 2018) and job recommendation system (Zhang et al 2016). Recommender systems in the labour market domain rely strongly on handcrafted features and expert knowledge, which make them costly, difficult to update and error-prone.…”