Due to the increasing number of graduates, many applicants experience the
situation about finding a job, and employers experience difficulty filtering
job applicants, which might negatively impact their effectiveness. However,
most job-hunting websites lack job recommendation and CV filtering or ranking
functionality, which are not integrated into the system. Thus, a smart job
hunter combined with the above functionality will be conducted in this project,
which contains job recommendations, CV ranking and even a job dashboard for
skills and job applicant functionality. Job recommendation and CV ranking
starts from the automatic keyword extraction and end with the Job/CV ranking
algorithm. Automatic keyword extraction is implemented by Job2Skill and the
CV2Skill model based on Bert. Job2Skill consists of two components, text
encoder and Gru-based layers, while CV2Skill is mainly based on Bert and
fine-tunes the pre-trained model by the Resume- Entity dataset. Besides, to
match skills from CV and job description and rank lists of jobs and candidates,
job/CV ranking algorithms have been provided to compute the occurrence ratio of
skill words based on TFIDF score and match ratio of the total skill numbers.
Besides, some advanced features have been integrated into the website to
improve user experiences, such as the calendar and sweetalert2 plugin. And some
basic features to go through job application processes, such as job application
tracking and interview arrangement