An E-Book Recommender System with Collaborative Filtering
Qingle Zeng · 2005
Collaborative filtering and content-based filtering are the most common information filtering technology in recommender system. Collaborative filtering is becoming the popular one and has been used widely because of its good quality. But traditional collaborative filtering algorithm has the shortcomings of sparsity,scalability and synonymy. In this paper,we present a new collaborative filtering algorithm base on the column-vector of the evaluations matrix for an e-book recommender system in the digital library. The algorithm computes the similarity of books instead of the shailarity of users,which can remarkably alleviate the workload. Our experiments suggest that the algorithm provides better performance than user-based algorithm.