文章基本信息

标题：Content-Based Recommendation for Web Personalization
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作者：R.Kousalya ; K.Saranya ; Dr.V.Saravanan 等
期刊名称：International Journal of Computer Technology and Applications
电子版ISSN：2229-6093
出版年度：2013
卷号：4
期号：6
页码：1038-1042
出版社：Technopark Publications
摘要：The amount of information available online is increasing exponentially. The existence of such abundance of information, in combination with the dynamic and heterogeneous nature of the web, makes web site exploration a difficult process for the average end user. One approach to satisfy the requirements of the user is to personalize the information available on the Web, called Web Personalization. Recommender systems have the effect of guiding users in a personalized way to interesting objects in a large space of possible options. In this paper, we aim at describing architecture of Content-based recommendation systems which try to recommend items similar to those a given user has liked in the past. Indeed, the basic process performed by a content-based recommender consists in matching up the attributes of a user profile in which preferences and interests are stored, with the attributes of a content object (item), in order to recommend to the user new interesting items
关键词：Web Personalization; Recommender Systems; Content-based Recommendation