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Due to the increasing number of graduates, many applicants experience thesituation about finding a job, and employers experience difficulty filteringjob applicants, which might negatively impact their effectiveness. However,most job-hunting websites lack job recommendation and CV filtering or rankingfunctionality, which are not integrated into the system. Thus, a smart jobhunter combined with the above functionality will be conducted in this project,which contains job recommendations, CV ranking and even a job dashboard forskills and job applicant functionality. Job recommendation and CV rankingstarts from the automatic keyword extraction and end with the Job/CV rankingalgorithm. Automatic keyword extraction is implemented by Job2Skill and theCV2Skill model based on Bert. Job2Skill consists of two components, textencoder and Gru-based layers, while CV2Skill is mainly based on Bert andfine-tunes the pre-trained model by the Resume- Entity dataset. Besides, tomatch 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 ofskill words based on TFIDF score and match ratio of the total skill numbers.Besides, some advanced features have been integrated into the website toimprove user experiences, such as the calendar and sweetalert2 plugin. And somebasic features to go through job application processes, such as job applicationtracking and interview arrangement.

JobHam-place with smart recommend job options and candidate filtering options