A user-friendly college recommending system using user-profiling and matrix factorization technique

Currently in India college ranking is the issue that is discussed a lot. In this paper, a common forum where students can get information about various engineering colleges and their ranking. There are many websites that give information about various engineering colleges but when it comes to students, for them it is important to know certain insights to parameters like faculty, campus life, hostel facility, placement etc. Students from small cities and villages have less exposure to various Colleges which are funded by state and central government for studies, Research and Innovation. If these students will have sufficient exposure then the young talent will be properly channelized as per their interest. In this we have developed a recommender system that understands information seeker need and accordingly generates recommendations for him/her through simple interface, which provides information to the students and advisors to improve the choice of courses. In our methodology we have opted for hybrid approach which combines advantages of Collaborative filtering algorithm and Content based filtering algorithm to improve our recommendations. The system consists of an interactive User Profiling [9] process in order to construct profile of the User. As the sample datasets that are used for experiments are large and also contain more number of feature sets, it is essential to understand dataset beforehand. Recommending items based on the users interest requires processing of these large datasets, thus if this information is properly profiled then the task of recommending would get a lot easier. Also when results are shown to the user, big challenge is how well data can be ranked so that user satisfaction is guaranteed.