Recommendation System for Library using Hybrid with Pearson’s Correlation and Slope One Algorithm

Abstract

Recommender System generates meaningful recommendations to users for items or products that might be interesting for them. It can help people to find interesting things and is widely used with the development of electronic commerce. In this paper, a hybrid collaborative filtering recommender is implemented the recommender system for library. In a university library, readers find it very difficult to search their favourite books. Even though they could possibly find the best preferred book by the user, searching another similar book to the first preferred book is difficult. So recommender system is required in a library. Pearson’s Correlation in Collaborative Filtering is used to find the similarity between the users and the active user. The Slope One algorithm is used to calculate the average difference in rating among pair of items. This system provides suggestions to the students in order to give the ratings on books which is related to their needs or targets. The readers can easily find the relevant books that they actually want or need.