福州大学学报（自然科学版）2017，Vol.45Issue(1)：25-31,7.DOI:10.7631/issn.1000-2243.2017.01.0025
融合相似用户和信任关系的动态反馈协同过滤推荐算法
Collaborative filtering recommendation algorithm of dynamic feedback combining similar users with trust relationship
摘要
Abstract
In order to overcome the shortcoming of the static characteristics in recommendation algorithms,the collaborative filtering recommendation algorithm of dynamic feedback combining similar users with trust relationship is proposed.The algorithm integrates similar users with trust relationship using dynamic factors,which are randomly initialized.The positive and negative feedback mechanism is established according to the error between user feedback and system prediction.In the light of the type of feedback,the value added or attenuation function is selected to properly adjust dynamic factors so that the systcm better predicts the user's score.Experiments using the real data set Epinions show that the dynamic fusion algorithm with the positive and negative feedback further improves the recommendation accuracy than that based on similar users or trust relationship.关键词
协同过滤推荐/相似用户/信任关系/动态融合Key words
collaborative filtering/similar users/trust relationship/dynamic fusion分类
信息技术与安全科学引用本文复制引用
高董英,邓新国,肖如良..融合相似用户和信任关系的动态反馈协同过滤推荐算法[J].福州大学学报（自然科学版）,2017,45(1):25-31,7.基金项目
国家自然科学基金资助项目(11501115) （11501115）
福建省出国留学奖学金资助项目(2015071003) （2015071003）
