A comprehensive survey of artificial intelligence techniques for talent analytics

C Qin, L Zhang, R Zha, D Shen, Q Zhang, Y Sun… - 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 …

[HTML][HTML] Human migration: The big data perspective

A Sîrbu, G Andrienko, N Andrienko, C Boldrini… - International Journal of …, 2021 - Springer
How can big data help to understand the migration phenomenon? In this paper, we try to
answer this question through an analysis of various phases of migration, comparing …

Mind the gender gap: Inequalities in the emergent professions of artificial intelligence (AI) and data science

E Young, J Wajcman, L Sprejer - New Technology, Work and …, 2023 - Wiley Online Library
The emergence of new prestigious professions in data science and artificial intelligence (AI)
provide a rare opportunity to explore the gendered dynamics of technical careers as they are …

A combined representation learning approach for better job and skill recommendation

VS Dave, B Zhang, M Al Hasan, K AlJadda… - Proceedings of the 27th …, 2018 - dl.acm.org
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 …

Attentive heterogeneous graph embedding for job mobility prediction

L Zhang, D Zhou, H Zhu, T Xu, R Zha, E Chen… - Proceedings of the 27th …, 2021 - dl.acm.org
Job mobility prediction is an emerging research topic that can benefit both organizations and
talents in various ways, such as job recommendation, talent recruitment, and career …

A hierarchical career-path-aware neural network for job mobility prediction

Q Meng, H Zhu, K Xiao, L Zhang, H Xiong - Proceedings of the 25th ACM …, 2019 - dl.acm.org
The understanding of job mobility can benefit talent management operations in a number of
ways, such as talent recruitment, talent development, and talent retention. While there is …

Job2Vec: Job title benchmarking with collective multi-view representation learning

D Zhang, J Liu, H Zhu, Y Liu, L Wang, P Wang… - Proceedings of the 28th …, 2019 - dl.acm.org
Job Title Benchmarking (JTB) aims at matching job titles with similar expertise levels across
various companies. JTB could provide precise guidance and considerable convenience for …

Predicting temporal sets with deep neural networks

L Yu, L Sun, B Du, C Liu, H Xiong, W Lv - Proceedings of the 26th ACM …, 2020 - dl.acm.org
Given a sequence of sets, where each set contains an arbitrary number of elements, the
problem of temporal sets prediction aims to predict the elements in the subsequent set. In …

A treatment engine by predicting next-period prescriptions

B Jin, H Yang, L Sun, C Liu, Y Qu, J Tong - Proceedings of the 24th ACM …, 2018 - dl.acm.org
Recent years have witnessed an opportunity for improving healthcare efficiency and quality
by mining Electronic Medical Records (EMRs). This paper is aimed at developing a …

Talent demand-supply joint prediction with dynamic heterogeneous graph enhanced meta-learning

Z Guo, H Liu, L Zhang, Q Zhang, H Zhu… - Proceedings of the 28th …, 2022 - dl.acm.org
Talent demand and supply forecasting aims to model the variation of the labor market, which
is crucial to companies for recruitment strategy adjustment and to job seekers for proactive …