Book recommender mobile application / Amir Imran Kamaludin - Kamaludin, Amir Imran (2021)
In this age where information is vast and huge, it is found to be difficult to find the right information from the enormous amount of data that is present and growing in the online platforms. Recommendation system solves this problem by automatically sorting through the massive amounts of data and identify user’s interest and makes the information searching much more easily. In this project, it presented a model for a personalized collaborative filtering book recommendation system. It are takes some information from user through signup which will help to get more appropriate recommendations based on individual user item rating and thus an attempt to overcome cold start problem. The item based collaborative filtering are used in this system with Cosine based similarity algorithm as the main algorithm.