摘要
传统多源监控信息挖掘方法研究信息挖掘深度较小、挖掘效率较低、投入消耗较大。为了解决上述问题,基于大数据分析技术研究了一种多源监控信息挖掘方法。该信息挖掘方法利用基础集成方法与奇异值算法处理数据并进行初步解析集成,提升数据收集的可靠性。采用不同的过滤方式加大对信息的协同过滤,降低干扰信息的影响,提高方法的挖掘效率。通过深入挖掘技术实现对信息数据的强化挖掘,达到对多源监控信息的挖掘目的。实验结果表明,基于大数据分析技术的多源监控信息挖掘方法,具备较高的信息挖掘深度,挖掘效率较高,符合信息挖掘发展的需求。
The traditional multi-source monitoring information mining method has the advantages of small depth,low efficiency and high cost.In order to solve the above problems,a multi-source monitoring information mining method is studied based on big data analysis technology.This information mining method uses the basic integration method and singular value algorithm to process data and carry out preliminary analysis integration,so as to improve the reliability of data collection.Different filtering methods are used to enhance the collaborative filtering of information,reduce the impact of interference information,and improve the mining efficiency of the method.Through in-depth mining technology to strengthen the mining of information data,to achieve the purpose of mining multi-source monitoring information.The experimental results show that the multi-source monitoring information mining method based on big data analysis technology has high depth of information mining,high efficiency of mining,and meets the needs of information mining development.
作者
尹旭熙
YIN Xu-xi(Information Engineering College of Guangzhou Huashang Vocational College,Guangzhou 511300,China)
出处
《电子设计工程》
2020年第17期52-55,60,共5页
Electronic Design Engineering
基金
校级科研项目(kjy2019023)
校级科研项目(kjy201602)
2016年广东省高等职业教育教学改革项目(20130201071)。
关键词
大数据分析技术
多源监控信息
信息挖掘
协同过滤
big data analysis technology
multi-source monitoring information
information mining
collaborative filtering
