摘要
文章对推荐系统进行了研究,借鉴了亚马逊的图书推荐思想。利用书籍的图书分类、书籍综合特征和书籍评分,提出了一种基于协同过滤、基于内容推荐的综合推荐算法。算法用于鉴别用户是否喜好某本书籍。同时将这种推荐算法应用于高校图书馆的书籍借阅系统中,旨在提高图书馆借阅系统的个性化。该算法能在一定程度上降低借阅者花费在借阅过程中的时间,另一方面能够通过推荐算法的应用,提高图书馆书籍利用率,降低书籍借阅过程中的马太效应。
This paper studies the recommendation system by Amazon＇s idea of recommending books. Using the classification of books, books＇comprehensive features and score of books, this paper proposes a comprehensive recommendation algorithm based on collaborative fihering and content - based recommendation. This algorithm is used to identify whether the user preferres to a book. At the same time, applying this recommendation algorithm to university library ＇s book borrowing system is to improve the personalization of library borrowing system. To some extent, this algorithm can reduce the time in the process of borrowing in the library. On the other hand, it can improve the utilization ratio of library books and reduce the Matthew effect in the process of borrowing books.
出处
《成都师范学院学报》
2014年第5期88-91,102,共5页
Journal of Chengdu Normal University
基金
云南省教育厅科学研究基金资助项目(2011y345)
关键词
推荐技术
协同过滤
内容推荐
个性化服务
recommendation technology
collaborative filtering
content recommendation
personalized service
