Decision Making Approach in Recruitment using Neuro-Fuzzy System

Abstract

Growing digitalisation in every aspect of business functioning has resulted in a need of automated systems to select the employee for the job. Rather than the traditional way of scanning the CVs personally and accessing them by the HR executives and subject matter experts(SME), a new computerized system which does the same but in less time is the need of the hour. Industries keep on hiring employees throughout the year to increase workforce and for that they require to shortlist the contenders from many applicants. This initial step requires segregation of the submitted resumes. Shortlisting resumes requires a panel of HR managers and field experts of the particular job field which check for the particular skills of individuals to select or score them by collective decision of group. This contains high uncertainty when it needs to be automated. The concepts of soft computation like Fuzzy Logic helps to deal with that kind of uncertainty and Neural network could be used to assign weights and then score the CVs to rank them. Using such hybrid system application would highly benefit the organisation to choose a quality employee based on his/her characteristics. It only requires requirements to be specified to the system which in turn would automate the ranking. General TermsDecision making neuro fuzzy algorithm

Neuro-Fuzzy Employee Ranking System in the Public Sector

“…The neuro fuzzy approach in the current research indicates that no human intervention is needed on order to adjust the initial data of the training data set. Employee evaluation and ranking has been detailed investigated and analyzed in recent bibliography [18], [19], [15]. In all cases the results were validated through extensive procedures but the subjectivity of the data due to selected output from human "experts" still resides in the equation.…”

Застосування Теорії Нечітких Множин Другого Типу Для Класифікації Та Ранжування Резюме

“…Використання нечітких логічних систем для вирішення завдань відбору, класифікації та прийняття рішень загального призначення стає дедалі популярнішим підходом. Було проведено дослідження низки робіт [1,2], в яких розглядається використання нечіткої логіки у системах прийняття рішень. У роботі [3] при створенні системи нечітких висновків автори використовували модель нечіткого контролера Мамдані для відбору кандидатів на отримання стипендій, базуючись на академічній успішності студентів.…”