个性化图书推荐研究

Research on Personalized Book Recommendation

个性化图书推荐系统通过对用户借阅行为的统计分析,获取用户的兴趣特征,实现由原来的人找书到书找人一对一的个性化图书推荐。现有的图书推荐系统各有侧重,图书推荐算法及评价标准各具优、缺点。未来,图书推荐的研究热点及难点将集中在借阅记录的稀疏性、新图书问题、高校新生问题、用户统计学信息、根据《中国图书馆分类法》计算图书相似性、副本数及借阅规章制度等方面。

By statistical analysis of the borrowing and reading behaviors of users,the personalized book recommendation system gets the interest characteristics of users and realizes the process of finding user for book instead of finding book for user.Each of the current personalized book recommendation system has its own priority.The future research hotspot and difficulty will focus on the sparsity of borrowing and reading,new arrivals,freshmen in universities,user statistics information,computing book similarity according to Chinese Library Classification,copy numbers,rules and regulations for borrowing and reading,and so on.