e-Recruitment recommender systems: a systematic review
MN Freire, LN de Castro - Knowledge and Information Systems, 2021 - Springer
Recommender Systems (RS) are a subclass of information filtering systems that seek to
predict the rating or preference a user would give to an item. e-Recruitment is one of the …
predict the rating or preference a user would give to an item. e-Recruitment is one of the …
Job recommender systems: A review
C De Ruijt, S Bhulai - arXiv preprint arXiv:2111.13576, 2021 - arxiv.org
This paper provides a review of the job recommender system (JRS) literature published in
the past decade (2011-2021). Compared to previous literature reviews, we put more …
the past decade (2011-2021). Compared to previous literature reviews, we put more …
Recruitpro: A pretrained language model with skill-aware prompt learning for intelligent recruitment
Recent years have witnessed the rapid development of machine-learning-based intelligent
recruitment services. Along this line, a large number of emerging models have been …
recruitment services. Along this line, a large number of emerging models have been …
Modeling two-way selection preference for person-job fit
Person-job fit is the core technique of online recruitment platforms, which can improve the
efficiency of recruitment by accurately matching the job positions with the job seekers …
efficiency of recruitment by accurately matching the job positions with the job seekers …
A combined representation learning approach for better job and skill recommendation
Job recommendation is an important task for the modern recruitment industry. An excellent
job recommender system not only enables to recommend a higher paying job which is …
job recommender system not only enables to recommend a higher paying job which is …
Learning to match jobs with resumes from sparse interaction data using multi-view co-teaching network
With the ever-increasing growth of online recruitment data, job-resume matching has
become an important task to automatically match jobs with suitable resumes. This task is …
become an important task to automatically match jobs with suitable resumes. This task is …
Skills prediction based on multi-label resume classification using CNN with model predictions explanation
KFF Jiechieu, N Tsopze - Neural Computing and Applications, 2021 - Springer
Skills extraction is a critical task when creating job recommender systems. It is also useful for
building skills profiles and skills knowledge bases for organizations. The aim of skills …
building skills profiles and skills knowledge bases for organizations. The aim of skills …
A challenge-based survey of e-recruitment recommendation systems
E-recruitment recommendation systems recommend jobs to job seekers and job seekers to
recruiters. The recommendations are generated based on the suitability of job seekers for …
recruiters. The recommendations are generated based on the suitability of job seekers for …
Characterizing the influence of graph elements
Influence function, a method from robust statistics, measures the changes of model
parameters or some functions about model parameters concerning the removal or …
parameters or some functions about model parameters concerning the removal or …
Aligning relational learning with lipschitz fairness
Relational learning has gained significant attention, led by the expressiveness of Graph
Neural Networks (GNNs) on graph data. While the inherent biases in common graph data …
Neural Networks (GNNs) on graph data. While the inherent biases in common graph data …