湖北工程学院学报2016，Vol.36Issue(3)：22-27,6.
基于隐式用户行为的推荐系统研究
Research of Recommendation System Based on Implicit User’s Behavior
摘要
Abstract
Users are often unconsciously influenced by the behavior of their friends because of the group behavior.Recommendation systems can be built through the relevant user’s behavior.By evaluating mining group users’information to build an implicit recommendation system algorithm,which con-sists of three parts,including the evaluation of communication activities based on implicit trust be-tween users,obtaining emotional keywords to infer user’s emotional level with the help of comments and using machine learning and regression algorithm to identify the level of emotion and the influence degree of trust between users and giving recommendations.By means of data analysis of the web-blog users’comments,this paper verifies the effectiveness of the algorithm and it may exactly reflect the implicit trust and the user mood so as to provide support for the decision recommendation system.关键词
推荐系统/隐式社会关系/信任度/用户情绪/支持向量机Key words
recommender system/implicit relationships/trust degree/users’emotion/SVM分类
信息技术与安全科学引用本文复制引用
卢军,张天凡..基于隐式用户行为的推荐系统研究[J].湖北工程学院学报,2016,36(3):22-27,6.基金项目
湖北省自然科学基金项目 （）
