【摘要】 文章抽取学校数据中心和有关信息系统的读者属性数据生成静态用户画像,采用基于关联规则的推荐算法分析读者借书记录,采用基于协同过滤推荐算法分析同伴借书记录生成动态用户画像及用户画像权重,再利用用户画像匹配新书的属性产生推荐结果,并按照画像权重排序,通过消息中心把个性化的推荐结果用邮件、微信或短信的形式发送给读者,同时读者可以进行新书预约,以提高新书推荐的针对性,加强图书馆对读者的了解。更多还原

【Abstract】 This paper generates static users profiles by attracting the readers’ attribute data from the data center of school and the relevant information system, analyzes the readers’ book borrowing records with recommendation algorithm based on association rules, generates dynamic users profiles and their weight by analyzing the associate’s book borrowing records based on collaborative filtration with recommendation algorithm, then matches the properties of new book with the users profiles to produce recommended results, and sort them by the weight of users profiles, send the personalized recommendation to the reader via e-mail, WeChat, SMS by message-center and enhances the pertinence of the recommended new books for the readers and also improve the understanding of the readers to the libraries.更多还原