SMART HIRE BASED SYSTEM

Abstract

An efficient and effective hiring process is a step-by-step process for hiring a new employee, whereby an organization identifies its talent needs, recruits from its talent pool and eventually hires the most qualified candidates. Most companies have their own hiring processes. What follows are the most common steps in the hiring process across industry and regardless of company size. Keep in mind, however, that the specific details of the hiring process are unique to each company. Our model is to Automate the interview process by using Machine learning in order to simplify the process by selecting the key words, skills, passions from the profile and sending the mails to the applicants. In most organisations, recruitment is a complex and time-consuming process, since they get a large number of job applications for openings that are called. managing those process applications manually would want a great amount of labour, time, and cash. further, the hr personnel or the recruitment group ought to manually shortlist the incoming candidates and time table interviews for them as a result. this lengthy technique makes the organization's operations inefficient. therefore, we deliberate to build a web-software with an aim to automate the interview system. the software consists of following capabilities which includes candidate character prediction the use of device gaining knowledge of, computerized resume parser, coping with of the scheduling of interviews, video recording in browser, test self assurance degree and other character trends of the candidate the use of video (eye movements and face feelings) and tone (speech) evaluation, hold track of the recruitment data and send mail to chose/rejected candidates robotically in one-click. this machine will as a consequence make the hiring technique plenty faster & smoother, allow recruitments in larger numbers, generate concise insights and offer summary of the candidate's profile with a purpose to encompass the resume, responses to questions, technical competencies, character traits, video and tone evaluation end result.