动静结合的图书馆个性化资源推荐系统的建立

Library Personalized Information Recommendation System Based on Dynamic and Static Interest Model

通过分析高校图书馆读者的基本信息、历史行为以及位置、信息环境等的变化,建立动态推荐和静态推荐相结合的个性化图书馆资源推荐系统。系统通过对图书馆信息资源提取关键字、分类和位置化,可以根据用户的兴趣模型和档案结合环境因素进行计算和信息推荐,不但为读者挖掘兴趣和推荐与兴趣相关的资源,节省读者搜索、查找时间,同时还可以提高图书馆资源的利用效率。

A library personalized information recommendation system was established based on a combination of dynamic and static model of user interest. The model was established by analyzing the user basic information, user historical behavior, location, information context, etc. At the same time, library resources were characterized by keyword, classification, catalog, etc. Then these resources were calculated and recommended to the matching library users. This system not only can help users find their interests, but also make library resources use efficiency to be improved.