Abstract:
A recruitment system comprises the processes, routines and elements essential to
speedy and effective hiring for an organization or for a company. A good recruitment
system includes all necessary features to aid management in hiring the best candidates for
open positions. An "e-Recruitment" system is also available for recruiters to advertise
jobs online where the applicants fill a form online and send or post their profiles. It is also
a strong and effective recruitment system. However, there are many difficulties such as
time-consuming and the lack of relevancy of job-matching. Online job recruitment
platform is one of the most prominent channels for both job seekers and recruiters to hunt
jobs and find suitable employees respectively. In the traditional job matching process,
manually scanning the resume or profile of a job seeker and matching the resume of job
seekers and requirements of job recruiters takes time-consuming and makes difficulties
for both seekers and recruiters. Thus, nowadays, many job recommendation systems and
cluster-based job matching systems appear. The studies applied k-means clustering for
providing the similar clusters of data but gives less relevant data. This system has
implemented a job matching system using k-means and word2vec that is to output the
clusters with semantically similar words. As a result, using k-means clustering and
word2vec model, recruiters can get the most relevant job seekers that fit employers‟
needs than k-means clustering only. And then, for the relevancy of job matching between
job seekers and job recruiters, the classification accuracy method has been used in this
system.
