摘要
【目的/意义】在利用用户感兴趣资源进行用户兴趣建模中,传统的资源特征选择方案未能体现用户真实兴趣,针对这一情况,提出一种基于认知的用户兴趣建模方法,改善个性化推荐效果。【方法/过程】在结合用户群体认知对资源特征进行识别的基础上,对用户感兴趣资源进行兴趣建模。以电影数据为例,进行个性化推荐实验,验证模型效果。【结果/结论】实验结果显示,基于认知的用户兴趣建模的推荐准确率明显高于传统基于项目的用户兴趣建模方法,该策略可以更准确地描述用户兴趣,提升用户兴趣建模效果。
【Purpose/significance】The traditional of resource features cannot reflect users'real interest when using resources that users interested in to construct user profiles modeling.To solve this problem,this paper proposes a user profiles modeling based on cognition to improve the effect of personalized recommendation.【Method/process】On the basis of recognizing the resource characteristics by considering the group cognition,we use resources that they are interested in to express users'interest,and verifies it by experiment based on movie data.【Result/conclusion】The results show that the effectiveness of user profiles modeling based on cognition is apparently better than item-based user profiles.Thus,it can be concluded that this model can describe users'interest more accurately,then improve the effect of user profiles modeling.
作者
石宇
胡昌平
时颖惠
SHI Yu;HU Chang-ping;SHI Ying-hui(School of Information Management,Wuhan Universitpy,Wuhan 430072,China)
出处
《情报科学》
CSSCI
北大核心
2019年第6期37-41,共5页
Information Science
基金
国家社会科学基金青年项目(17CTQ024)
关键词
个性化推荐
用户认知
用户兴趣建模
personalized recommendation
user cognition
user profiles modeling
