Abstract: Nowadays many major e-commerce websites are using recommendation systems to provide relevant suggestions to their customers. The recommendation could be based on various parameters such as items popular on the companies websites. Consider buying a book where reader usually goes to book store personally and selects a book, it takes so much time to go through all the books and select one book out of it. This is very time consuming process and after that also there is no guarantees that the person will get the book he really wanted. There is requirement of system which consumes less time and gives higher probability of what reader wants. Hence we are proposing a web recommendation system for book readers, which will recommend book depending upon previous choices made by reader and readers profile. The proposed recommendation system will give its users the ability to view and search books as well as novels which will be use to draw out conclusions about the stream and genre of the books liked by the user. The system will analyse the user behaviour by using multiple recommendation techniques like content based algorithm, Time sequence based collaborative filtering.
Keywords: Books, Content based algorithm, Time sequence based collaborative filtering.