155 citations · 318 across the 12 of their papers we have counts for
6 papers · 1 filter
DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation
Xiaoshan Yu, Chuan Qin, Qi Zhang +4
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the significant challenge of quickly and acc…
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
Xiao Han, Chen Zhu, Xiao Hu +3
Job recommender systems are crucial for aligning job opportunities with job-seekers in online job-seeking. However, users tend to adjust their job preferences to secure employment…
Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation
Wenxuan Zhang, Hongzhi Liu, Yingpeng Du +4
Generative large language models(LLMs) are proficient in solving general problems but often struggle to handle domain-specific tasks. This is because most of domain-specific tasks,…
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
Chao Wang, Hengshu Zhu, Chen Zhu +2
The recent development of online recommender systems has a focus on collaborative ranking from implicit feedback, such as user clicks and purchases. Different from explicit ratings…
Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning
Chen Zhu, Hengshu Zhu, Hui Xiong +4
Person-Job Fit is the process of matching the right talent for the right job by identifying talent competencies that are required for the job. While many qualitative efforts have b…
Collaborative Company Profiling: Insights from an Employee's Perspective
Hao Lin, Hengshu Zhu, Yuan Zuo +3
Company profiling is an analytical process to build an indepth understanding of company's fundamental characteristics. It serves as an effective way to gain vital information of th…