Collaborative filtering model of book recommendation system. (2016) - Guo, Xiaoqiang; Feng, Lichao; Liu, Yalou; Han, Xiuli
With the rapid development of information technology and internet, people from an era of scarcity gradually entered the era of information overload. For information-consumers, finding themselves interested in information from a large amount of information is a very difficult task. As regard to information producers, letting the production information stand out and getting the attention of the masses of users is also a very difficult task. To solve this contradiction, first, we establish a decorrelation principal component analysis model based on the correlation theory to obtain the main factors affecting the user evaluation of books. Secondly, we establish a predictive scoring system based on linear regression theory which can predict book ratings. Finally, we establish a collaborative filtering model of book recommendation.