摘要
在网络用户和网络产品急剧攀升的背景下,非个性化产品推荐成为一种很好的网络广告手段,已有的研究中,Vague集方法已被应用于推荐系统中,并取得了较好的效果。分析了非个性化产品推荐的一般特征和优点;借助Vague值描述的产品,研究了特征值方法和"马太效应"记分函数方法运用于产品排序的可行性;最后,通过实例验证了两种方法的在非个性化产品推荐中的有效性和一致性。
Non-personalized recommender systems has become a popular online advertising method due to the comprehensive applications of users and products. In the previous research, Vague value method has been used to study the recommender system, which is approved to be used in this field. The general characteristics and advantages of non-personalized recommender are reviewed. Hence, the feasibilities of using eigenvalue method and the ＂Matthew Effect＂ score function method in products-ranking are studied based on description of products by Vague set. The effectiveness and coconscious of two methods are then proved with examples.
出处
《计算机工程与应用》
CSCD
2012年第13期63-66,共4页
Computer Engineering and Applications
基金
河南省科技厅基础与前沿课题
河南省教育厅基础与前沿课题
关键词
非个性化推荐
VAGUE值
特征值
“马太效应”函数
non-personalized recommender systems
Vague value
eigenvalue
＂Matthew Effect＂ score function
