摘要
针对传统互联网发展中信息量不断增加,传统推荐平台遇到计算瓶颈的问题,提出了基于互联网+的多能融合个性化方案推荐平台。首先,对个性化方案推荐平台结构进行分析,并且分析用户的行为。通过用户行为的分析创建基于用户兴趣偏好的推荐模型,对推荐算法进行描述。最后,设计基于用户兴趣变化过滤推荐模型,对设计的平台进行测试。通过测试结果表示,此模型能够避免传统算法的不足,使应用平台综合推荐性能得到提高。
In view of the increasing amount of information in the development of traditional Internet,the traditional recommendation platform has encountered the bottleneck of computing. Firstly,the structure of personalized scheme recommendation platform is analyzed,and the behavior of users is analyzed.Through the analysis of user behavior,a recommendation model based on user interest preference is created to describe the recommendation algorithm. Finally,we design a filter recommendation model based on the change of user interest,and test the platform. The test results show that this model can avoid the shortcomings of traditional algorithms and improve the comprehensive recommendation performance of the application platform.
作者
郇长武
朱琳
陈俊材
周锋奇
张智勇
XUN Chang wu;ZHU Lin;CHEN Jun cai;ZHOU Feng qi;ZHANG Zhi yong(Guangzhou Haishu Software Co.,Ltd.,Guangzhou 510660,China)
出处
《电子设计工程》
2020年第8期30-33,38,共5页
Electronic Design Engineering
基金
广州市科技计划项目(2018-0613-ZB-0039)。
关键词
互联网+
多能融合
算法研究
个性化推荐
Internet+
multi energy fusion
algorithm research
personalized recommendation
