摘要
针对以往使用的内容过滤推荐系统、数据挖掘技术推荐系统难以区分信息属性,导致系统不同分区所占比例与实际不符,出现推荐精准度低的问题,提出了智能运维平台协同过滤信息推荐系统设计。根据系统硬件结构,从超文本服务器中阅读位置信息,构建索引器,在同一上下文中,正向索引和反向索引关键词。使用华为云Stack8.0平台中央处理器,设计平台端信息查询电路,用于查询输入输出信息。使用机器学习方法,明确任务执行计划,剔除噪声信息,依据关联规则,完成协同过滤信息推荐系统设计。由实验结果可知,该系统受到噪声影响程度较小,最高推荐精准度为95%,具有精准推荐效果.
In view of the difficulty in distinguishing information attributes in the previous content filtering recommendation system and data mining recommendation system,the proportion of different partitions of the system is inconsistent with the actual situation,and the recommendation accuracy is low.The design of collaborative filtering information recommendation system based on intelligent operation and maintenance platform is proposed.According to the hardware structure of the system,the location information is read from the hypertext server,and the indexer is constructed.In the same context,forward index and reverse index keywords.The central processor of Huawei cloud Stack8.0 platform is used to design the platform side information query circuit,which is used to query the input and output information.Using machine learning method,clear task execution plan,eliminate noise information,according to association rules,complete collaborative filtering information recommendation system design.The experimental results show that the system is less affected by noise,and the highest recommendation precision is 95%,which has accurate recommendation effect.
作者
张耀
王丹丹
梁志远
崔晓萌
ZHANG Yao;WANG Dandan;LIANG Zhiyuan;CUI Xiaomeng(State Grid Tianjin Electric Power Company,Tianjin 300010,China;Tianjin Sanyuan Electric Information Technology Co.,Ltd.,Tianjin 300010,China)
出处
《电子设计工程》
2022年第3期49-53,共5页
Electronic Design Engineering
关键词
智能运维平台
协同过滤
信息推荐系统
机器学习
intelligent operation and maintenance platform
collaborative filtering
information recomme⁃ndation system
machine learning
