AI-Based Internship Recommendation Engine for PM Internship Scheme

Abstract

Many students from rural or underserved communities who want to apply for an internship do not have much information or guidance available to them that will help them identify and choose a suitable internship opportunity. Additionally, given that many of the students come from a rural area, they have limited exposure and experience to using digital media; therefore, they may not be aware of how to successfully apply for internships through a website that requires some technical expertise. This paper presents an internship recommendation engine (IRE), which utilizes artificial intelligence (AI), to provide customized recommendations for potential candidates based on their education, skills, interests, and desired location. The proposed AI-based IRE system would provide candidates with accurate recommendations based on the candidate’s education and skills/abilities and the candidate’s interests and the parameters in which the candidate wants to receive a recommendation for an internship. Once the IRE has completed the analysis, it would display the recommended internship to the candidate through their account on the IRE system. In order to provide the candidate with the best internship recommendation, the IRE system employs a hybrid recommendation engine approach—encompassing both content-based filtering and collaborative filtering—to yield accurate recommendations.