计算机工程与应用2018，Vol.54Issue(9)：116-120,5.DOI:10.3778/j.issn.1002-8331.1612-0157
基于多分段改进PCC的协同过滤算法
Collaborative filtering algorithm based on improved multi-segmented PCC
摘要
Abstract
With the rapid development of the Internet,a large variety of information has exploded,and resulting in infor-mation overload. Now, by analyzing a large number of available information, recommender systems can help users find things they are interested.And collaborative filtering is the most widely used approach in the recommendation systems. However,its accuracy of recommendation is still needed to be improved.In this paper,a novel effective collaborative filtering algorithm based on segmented and improved PCC is proposed to improve the accuracy of the recommendation system.The number of co-items and the PCC threshold is used to calculate and improve the results of the PCC in this method.Finally,the experimental results show that the proposed method is better than other traditional methods.关键词
推荐系统/协同过滤/相似度/分段Key words
recommender system/collaborative filtering/similarity/segmentation分类
信息技术与安全科学引用本文复制引用
张沪寅,段维,叶刚..基于多分段改进PCC的协同过滤算法[J].计算机工程与应用,2018,54(9):116-120,5.基金项目
国家自然科学基金(No.61540059) （No.61540059）
深圳市科技计划项目(No.JCYJ20140603152449639). （No.JCYJ20140603152449639）
