Abstract
Recommender systems have emerged as critical tools that help alleviate the burden of information overload for users. Since these systems have to deal with a variety of modes of user interactions, collaborative recommendation must be sensitive to a user’s specific context and changing interests over time. Our approach is to build a digital library system containing soft copies in form of PDF, PPT etc. To make it more efficient we are adding recommendation system that will suggest books to students on their issuance history, rating patterns and viewing of books. Our idea here is to apply a hybrid recommendation system that combines effective individual recommendation algorithms.
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