Collaborative filtering model of book recommendation system

被引：0

作者：

Guo X. ^{[1
]}

Feng L. ^{[1
]}

Liu Y. ^{[2
]}

Han X. ^{[2
]}

机构：

[1] North China University of Science and Technology, Tangshan, Hebei

[2] College of Mining Engineering, North China University of Science and Technology, TangShan

来源：

International Journal of Advanced Media and Communication | 2016年 / 6卷 / 2-4期

关键词：

Collaborative filtering; Principal component analysis; Regression prediction;

D O I：

10.1504/IJAMC.2016.080974

中图分类号：

学科分类号：

摘要：

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. Copyright © 2016 Inderscience Enterprises Ltd.

引用

页码：283 / 294

页数：11

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