基于数据挖掘的移动用户个性化推荐系统研究与设计

Research and design of mobile user personalized recommendation system based on data mining

通过数据挖掘方法提取用户感兴趣的资源信息,可以实现移动用户的个性化推荐。在此设计基于数据挖掘的移动用户个性化推荐系统,构建移动用户个性化推荐的评价指标体系,通过自适应学习控制进行资源池数据挖掘,采用虚拟仪器软件结构设计方法设计移动用户的个性化推荐系统的底层函数库,对移动用户个性化推荐系统的I/O接口进行软件设计,设计个性化推荐系统的程序驱动和底层函数库,实现移动用户个性化推荐系统的软件的优化设计。实验结果表明,该系统进行资源池中的数据挖掘和移动用户的个性化推荐,数据关联属性的匹配度较高,提高了推荐的准确性和关联性,系统可靠稳定。

The mobile user＇s personalized recommendation can be realized by extractiing the resource information interested by users with the data mining method. The mobile user personalization recommendation system based on data mining was de- signed. The evaluation index system for mobile user personalized recommendation was constructed. The resource pool data min- ing is performed by the adaptive learning control. The bottom function library of mobile user personalization recommendation sys- tem is designed with the software architecture design method for virtual instruments. The software for I/O interface of the mobile user personalization recommendation system and the program driving of personalized recommendation system are designed, sys- tem optimization design of the software for the mobile user personalized recommendation was realized. The system test results show that the system has high matching degree of data correlation attributes in data mining in resource pool and mobile user＇s personalized recommendation, which has improved the accuracy and relevance of the recommendation. It is reliable and stable.