Recently, recruiters have find the taxing to communicate with all their candidates about the interview process and it results in the hassle of conducting interviews. Also, in cases, where there are large volumes of applicants, communicating with thousands of candidates and conducting other screening duties add to the heap of recruitment problems. The proposed system, JARO addresses the common concerns that a candidate faces when it comes to attend the mass interviews. Some of the challenges faced are inconsistency in questions, different days, different times of the day, interviewer's mood, venue of the interview and the list goes on. Therefore, JARO accelerates the interview process towards an unbiased decision-making process by proposing a chatbot that would conduct interviews by analyzing the candidates Curriculum Vitae (CV), based on which, it then prepares a set of questions to be asked to the candidate. The system will consist of features like resume analysis and automatic interview processes. The software would also ask questions based on the previous responses of the candidate by utilizing a Natural Language Processing (NLP) model which is very helpful in this process. After the interview process, the software would analyze the data collected to determine the right choice for the position offered. Thus, the project, JARO chatbot mainly intends to streamline the process of hiring employees.
Software And Hardware
Textual Question Answering for Semantic Parsing in Natural Language Processing