论文部分内容阅读
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。
By analyzing the basic information, historical behavior, location and information environment of university library readers, a personalized library resource recommendation system combining dynamic recommendation and static recommendation is established. By extracting key words, classifying and locating the information resources of the library, the system can calculate and recommend information according to the user’s interest model and the file in combination with the environmental factors, so as to not only discover the interests and recommend the resources related to the interests of the readers, but also save the readers’ searching, Find time, but also can improve the utilization efficiency of library resources.