Abstract: Choosing a right project is always a difficult for students as well as for professionals due to lack of right guidance, a mismatch between one’s skills, experience, interests and project required. Hence it causes low performance and ineffective results. To overcome this problem, we have designed an innovative concept for project recommendation system which recommends projects to users based on their skills, interests and experience. The objective of this paper is to highlight the current trend in project recommendation systems which addresses the problems faced by users and recommends best possible results by applying Machine Learning algorithms like content, based filtering, Cosine Similarity and TF- IDF Vectorisation in order to match interests of users with project requirements. The System resulted in achieving an overall average accuracy of 72.4 % match.

Keywords: Machine Learning, Project recommendation, Content-based filtering, TF-IDF, Cosine similarity.

Downloads: | DOI: 10.17148/IARJSET.2026.13212