Resume summarization and social media mining for shortlisting eligible candidates

Abstract

Human Resource Management is very import part of any organization. In todays environment, if organization wants to survive and expand their busi ness, they have to recruit people with skills experience and quali cation, but nding such kind of candidates are crucial and costly for an organization. For limited vacancies if an organization receives a few resumes than it is possible to analyses these applicants skills, background and experiences, but when for limited vacancies an organization receives thousands of applications, then analyzing each and every resumes in depth is very time consuming and tedious task. Nowadays, employer also checks the background of the can didates for future safety. Social networking site helps to investigate their personal and professional pro le. By doing this employer may come to know that the particular candidate is suitable for the current job opening or not. To ful ll such kind of idea, HR person have to manually check their pro les in di erent social media networks. This process of checking background and screening resume is very time consuming. In order to speed up the process of screening and track candidate on social media networks, this research intro duces a utility which can helps in analyzing thousands of resumes based on pre-entered criteria and as a result it gives a bunch of resumes that has met the criteria. By this method, HR can shortlist the resumes for the further consideration. With the help of Social Media data, one can identify candi dates likes, dislikes and relationship in society, like LinkedIn helps to track the professional pro le of a candidate. Thus, this utility helps in analyzing candidates social media details (Facebook, LinkedIn) if the details are avail able at the public level. We can say that with the help of natural language processing and social media network we can select talented candidates and also reduce the manual work