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 …

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 …

Large Language Models (LLMs) have revolutionized natural language processing tasks,
demonstrating their exceptional capabilities in various domains. However, their potential for …

Recommending suitable jobs to users is a critical task in online recruitment platforms. While
existing job recommendation methods encounter challenges such as the low quality of …

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 …

The rapid development of online recruitment services has encouraged the utilization of
recommender systems to streamline the job seeking process. Predominantly, current job …

The task of multi-behavioral sequential recommendation (MBSR) has grown in importance
in personalized recommender systems, aiming to incorporate behavior types of interactions …

With the rapid development of online recruitment platforms, a variety of emerging
recommendation services have been witnessed for benefiting both job seekers and …

Reciprocal Recommender Systems (RRSs) which aim to satisfy the preferences of both
service providers and seekers simultaneously has attracted significant research interest in …

Reciprocal recommender system (RRS), considering a two-way matching between two
parties, has been widely applied in online platforms like online dating and recruitment …