摘要：This paper presents a recommender system for web documents (given
as bookmarks). The system uses for classification a combination of content,
event and collaborative filters and for recommendation a modified Pearson-r
algorithm. The algorithm for recommendation is using not only the correlation
between users but also the similarity between classes. Some experimental results
that support this approach are also presented.
