A book recommendation system based on popularity, correlation and collaborative filtering.
Recommendation systems are information filtering systems that deal with the problem of information overload by filtering vital information fragments out of large amounts of dynamically generated information according to a user’s preferences, interest, or observed behavior about a certain item. A recommendation system has the ability to predict whether a particular user would prefer an item or not based on the user’s profile.
The aim of this project is to build a book recommendation system that can provide interesting book recommendations to the user based on a book's popularity or the user's interests/preferences.
The eventual result of the book recommendation system is not to make accurate predictions but instead to provide difficult to quantify insightful book recommendations.