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 …

A challenge-based survey of e-recruitment recommendation systems

Y Mashayekhi, N Li, B Kang, J Lijffijt… - ACM Computing Surveys, 2024 - dl.acm.org
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 …

Towards the evaluation of recommender systems with impressions

FB Perez Maurera, M Ferrari Dacrema… - Proceedings of the 16th …, 2022 - dl.acm.org
In Recommender Systems, impressions are a relatively new type of information that records
all products previously shown to the users. They are also a complex source of information …

Contentwise impressions: An industrial dataset with impressions included

FB Pérez Maurera, M Ferrari Dacrema… - Proceedings of the 29th …, 2020 - dl.acm.org
In this article, we introduce the\dataset dataset, a collection of implicit interactions and
impressions of movies and TV series from an Over-The-Top media service, which delivers its …

Self-attentional multi-field features representation and interaction learning for person–job fit

M He, D Shen, T Wang, H Zhao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Person–job fit, which aims to predict the matching degree between a resume and a job, has
become an effective way to overcome information overload in the recruitment market …

PrivateJobMatch: a privacy-oriented deferred multi-match recommender system for stable employment

A Saini, F Rusu, A Johnston - Proceedings of the 13th ACM Conference …, 2019 - dl.acm.org
Coordination failure reduces match quality among employers and candidates in the job
market, resulting in a large number of unfilled positions and/or unstable, short-term …

Boolean kernels for collaborative filtering in top-N item recommendation

M Polato, F Aiolli - Neurocomputing, 2018 - Elsevier
In many personalized recommendation problems available data consists only of positive
interactions (implicit feedback) between users and items. This problem is also known as One …

Impression-aware recommender systems

FBP Maurera, MF Dacrema, P Castells… - arxiv preprint arxiv …, 2023 - arxiv.org
Novel data sources bring new opportunities to improve the quality of recommender systems.
Impressions are a novel data source containing past recommendations (shown items) and …

A job recommendation model based on a two-layer attention mechanism

Y Mao, S Lin, Y Cheng - Electronics, 2024 - mdpi.com
In the field of job recruitment, traditional recommendation methods only rely on users' rating
data of positions for information matching. This simple strategy has problems such as low …

Impression-Aware Recommender Systems

FB Perez Maurera, M Ferrari Dacrema… - ACM Transactions on …, 2023 - dl.acm.org
Novel data sources bring new opportunities to improve the quality of recommender systems
and serve as a catalyst for the creation of new paradigms on personalized …