This paper provides a review of the job recommender system (JRS) literature published in
the past decade (2011-2021). Compared to previous literature reviews, we put more …

Recommendation systems usually involve exploiting the relations among known features
and content that describe items (content-based filtering) or the overlap of similar users who …

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 …

Finding acceptable applicants for a vacant job might be a difficult process, especially when
there are many prospects. The manual process of screening resumes could stymie the …

In this paper, we propose a content-based recommendation Algorithm which extends and
updates the Minkowski distance in order to address the challenge of matching people and …

In the field of job recruitment, a classic recommendation system consists of users, positions,
and user ratings on positions. Its key task is to predict the unknown rating data of users on …

Job titles are the most fundamental building blocks for occupational data mining tasks, such
as Career Modelling and Job Recommendation. However, there are no publicly available …

This work is an attempt to collate the data and discover the foremost relevant candidate-job
association mapping concurring with the skills, interests, and preferences of a user and to …

In a high mobility job market, accumulated historical sequences information from persons
and jobs bring opportunities and challenges to person-job matching recommendation …

One of the current job recruiter's biggest challenges is to filter the right candidate's resume
over the pool of resumes. For a single job post, many times more than thousands of …