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.
