摘要
为给图书馆用户提供更个性化的推荐服务,引进Spark框架设计图书馆个性化服务系统。首先,请求录入用户注册系统后在图书馆中的主动浏览行为,过滤无用信息,实现用户个性化行为提取;其次,设计图书馆服务类目服务请求分发程序,根据用户提出的主动服务需求,响应其请求并提供推荐服务;最后,引进协同过滤算法,设计面向用户的个性化服务项目主动推荐行为,完成系统开发。实验结果表明,开发的服务系统可以提高推荐服务项目与用户需求项目之间的适配度,从而满足图书馆用户对服务的个性化服务需求。
In order to provide library users with more personalized recommendation services, the Spark framework is introduced to design the library personalized service system. Firstly, request input user registration system after active browsing behavior in the library,filter useless information, achieve user personalized behavior extraction. Secondly, design the service request distribution program of library service category, respond to users’ requests and provide recommended services according to their active service requirements. Finally, the collaborative filtering algorithm is introduced to design a user-oriented personalized service item active recommendation behavior, and the system development is completed. The experimental results show that the developed service system can improve the compatibility between the recommended service items and the user’s demand items, so as to meet the library users’ demand for personalized service.
作者
陆慧
LU Hui(School of Information Technology,Anhui Finance&Trade Vocational College,Hefei Anhui 230601,China)
出处
《信息与电脑》
2022年第20期44-46,共3页
Information & Computer