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 …

The widespread use of online recruitment services has led to an information explosion in the
job market. As a result, recruiters have to seek intelligent ways for Person-Job Fit, which is …

In recent years, there has been growing interest in recommendation systems, which is
matched by their widespread adoption across various sectors. This can be attributed to their …

Recommender systems can help correlate information and recommend personalised
services to users as a general information filtering tool. However, contextual factors …

The task of job recommendation has been invariably solved using either a filter-based
technique or through recommender systems where categorical features associated with jobs …

While searching for consumer goods, users frequently ask for suggestions from their peers
by writing short free-form textual requests. For example, when searching for movies users …

The growth of online job-posting repositories provided job-seekers with access to a large
number of potential jobs. User assessment of recommended jobs becomes especially a …

The ranking algorithm in the recommender system aims at optimizing accuracy during
training so that it pays too much attention to the relevance of the individual and ignores the …

Many recommendation algorithms are available to digital library recommender system
operators. The effectiveness of algorithms is largely unreported by way of online evaluation …

For the task of job recommendations, common practice is to recommend job postings to job
seekers, and recently different embedding techniques have been applied to solve this task …