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 …
Predicting employee attrition using tree-based models
Purpose The purpose of this study is to develop tree-based binary classification models to
predict the likelihood of employee attrition based on firm cultural and management …
predict the likelihood of employee attrition based on firm cultural and management …
DOMFN: A divergence-orientated multi-modal fusion network for resume assessment
In talent management, resume assessment aims to analyze the quality of a job seeker's
resume, which can assist recruiters to discover suitable candidates and benefit job seekers …
resume, which can assist recruiters to discover suitable candidates and benefit job seekers …
Resumegan: an optimized deep representation learning framework for talent-job fit via adversarial learning
Nowadays, it is popular to utilize online recruitment services for talent recruitment and job
recommendation. Given the vast amounts of online talent profiles and job-posts, it is labor …
recommendation. Given the vast amounts of online talent profiles and job-posts, it is labor …
Talent recommendation based on attentive deep neural network and implicit relationships of resumes
Y Huang, DR Liu, SJ Lee - Information Processing & Management, 2023 - Elsevier
Talent recruitment has become a crucial issue for companies since finding suitable
candidates from the massive data on potential candidates from online talent platforms is a …
candidates from the massive data on potential candidates from online talent platforms is a …
Modelci-e: Enabling continual learning in deep learning serving systems
MLOps is about taking experimental ML models to production, ie, serving the models to
actual users. Unfortunately, existing ML serving systems do not adequately handle the …
actual users. Unfortunately, existing ML serving systems do not adequately handle the …
NLP-based resume screening and job recruitment portal
R Kadam, G Suhas, U Mukri, S Khandare - Data Intelligence and …, 2022 - Springer
Organizations get a large number of resumes for each job opening, and they employ resume
or archive screeners to select the competent and exceptional applicants. However, resume …
or archive screeners to select the competent and exceptional applicants. However, resume …
An efficient resume skill extraction using deep feature-based AGT optimized K means clustering
JH Priyanka, N Parveen - Multimedia Tools and Applications, 2024 - Springer
When developing a job recommender system, skill extraction is crucial. It may also be used
to create talent profiles and knowledge bases for companies. To address this issue, several …
to create talent profiles and knowledge bases for companies. To address this issue, several …
[HTML][HTML] CareerMiner: Automatic extraction of professional network from large Chinese resume data
Q Chen, D Kong, Y Zhu, Z Shen, C Lu, Y Li, L Zhang - Franklin Open, 2024 - Elsevier
The professional contacts of a person, including their past colleagues and supervisors, can
play an important role in job recommendation and intelligent human resources …
play an important role in job recommendation and intelligent human resources …
Screening and Ranking resume's using Stacked Model
D Kavitha, B Padmavathi, V Sushanth… - … on Advances in …, 2023 - ieeexplore.ieee.org
Finding the top candidates for a position is the aim of the resume screening process. The
application must make use of machine learning methodologies as well as natural language …
application must make use of machine learning methodologies as well as natural language …