计算机工程2011，Vol.37Issue(19)：59-61,3.DOI:10.3969/j.issn.1000-3428.2011.19.018
基于单分类的协同过滤推荐算法
Collaborative Filtering Recommendation Algorithm Based on Single-class Classification
摘要
Abstract
With the increasing number of users and goods in E-commerce recommender systems, the data set sparse of user goods rating reduces the quality recommendation of collaborative filtering recommendation algorithm. To solve this problem, this paper proposes a collaborateive filtering recommendation algorithms based on single-class classificatin. It chooses candidate nearest neighbor set which depending on the target user rating goods corresponding to category and uses single-class classification to predict the values of the user rating. It can reduce the sparse of data set which is formed by the target user and the candidate nearest. Experimental results show that the algorithm is able to increase the accuracy of searching nearest neighbor set, resulting in improving recommendation quality of the collaborative filtering.关键词
推荐系统/协同过滤/数据稀疏性/单分类/平均绝对偏差Key words
recommendation system/ collaborative filtering/ data sparse/ single-class classification/ Mean Absolute Error(MAE)分类
信息技术与安全科学引用本文复制引用
杨帅,薛文,谢永红,王晓宇,祝小杰..基于单分类的协同过滤推荐算法[J].计算机工程,2011,37(19):59-61,3.基金项目
国家自然科学基金资助项目(60675030,60875029) （60675030,60875029）
