摘要
由于大规模动态数据集在推荐时难以兼顾推荐准确度的问题,该文在充分考虑用户所处上下文情景因素,提出一种基于上下文的协同过滤推荐技术,以提高用户偏好的预测准确度。实验表明,该技术能有效提高推荐质量和效率。
Due to large scale dynamic data set between recommendation accuracy problem when recommended, in this paper, give full consideration to the user in a context situational factors, proposes a collaborative filtering recommendation technology based on the context, in order to improve the prediction accuracy of user preference. Experiments show that the technology can effectively improve the recommendation quality and efficiency.
出处
《电脑知识与技术》
2015年第9X期174-175,共2页
Computer Knowledge and Technology
基金
贵州省科技技术基金项目
项目编号:黔科合LH字[2014]7439号
关键词
协同过滤
推荐准确度
时间上下文
Collaborative Filtering(CF)
recommendation accuracy
time context
