A comprehensive survey of artificial intelligence techniques for talent analytics

C Qin, L Zhang, Y Cheng, R Zha, D Shen… - arXiv preprint arXiv …, 2023 - arxiv.org
In today's competitive and fast-evolving business environment, it is a critical time for
organizations to rethink how to make talent-related decisions in a quantitative manner …

A survey on semantic processing techniques

R Mao, K He, X Zhang, G Chen, J Ni, Z Yang… - Information …, 2024 - Elsevier
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

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 …

Knowledge graphs in education and employability: A survey on applications and techniques

Y Fettach, M Ghogho, B Benatallah - IEEE Access, 2022 - ieeexplore.ieee.org
Studies on the relationship between education and employability are of paramount
importance for policy makers, training institutions, companies and students. The availability …

Transferrable framework based on knowledge graphs for generating explainable results in domain-specific, intelligent information retrieval

H Abu-Rasheed, C Weber, J Zenkert, M Dornhöfer… - Informatics, 2022 - mdpi.com
In modern industrial systems, collected textual data accumulates over time, offering an
important source of information for enhancing present and future industrial practices …

Data science for job market analysis: A survey on applications and techniques

I Rahhal, I Kassou, M Ghogho - Expert Systems with Applications, 2024 - Elsevier
The job market is evolving continuously due to changes in economic landscapes,
technological improvements, and skill requirements. In the era of digitalization, a wealth of …

UISA: User Information Separating Architecture for Commodity Recommendation Policy with Deep Reinforcement Learning

A Xu, L Jian, Y Yin, N Zhang - ACM Transactions on Recommender …, 2024 - dl.acm.org
Commodity recommendation contributes an important part of individuals' daily life. In this
context, deep reinforcement learning methods have demonstrated substantial efficacy in …

A Co-design Study for Multi-stakeholder Job Recommender System Explanations

R Schellingerhout, F Barile, N Tintarev - World Conference on Explainable …, 2023 - Springer
Recent legislation proposals have significantly increased the demand for eXplainable
Artificial Intelligence (XAI) in many businesses, especially in so-called 'high-risk'domains …

Recall, expand and multi-candidate cross-encode: Fast and accurate ultra-fine entity typing

C Jiang, W Hui, Y Jiang, X Wang, P Xie… - arXiv preprint arXiv …, 2022 - arxiv.org
Ultra-fine entity typing (UFET) predicts extremely free-formed types (eg, president, politician)
of a given entity mention (eg, Joe Biden) in context. State-of-the-art (SOTA) methods use the …

[PDF][PDF] Semantic Approaches Survey for Job Recommender Systems.

A Brek, Z Boufaida - RIF, 2022 - ceur-ws.org
Newly, the e-recruitment phenomenon has been widely spread, which led to the increase of
job descriptions online and caused a remarkable growth in the number of jobs seekers …