摘要
常规系统过滤网络大数据信息时,存在过滤数据量少、过滤精度和过滤效率低的问题。因此,本文提出基于物联网的网络大数据信息过滤系统。硬件方面,应用物联网抓取网络大数据,根据功能性设计各个模块包括数据存储、分布式数据过滤、用户查询处理、网络大数据抓取以及区域模型构建,组成系统总体硬件结构;软件方面,优化信息过滤算法,降噪处理物联网大数据,聚类分析数据类别,计算簇内数据与聚类中心的距离,过滤距离值较大的虚假无效数据。抓取社交网络软件关键词数据,设置对比实验。实验结果表明,本文设计的系统增加了网络大数据的信息过滤量,提高了过滤精度和过滤速度。
When filtering network big data information in conventional systems, there are some problems, such as small amount of filtered data, low filtering accuracy and low filtering efficiency. Therefore, this paper proposes a network big data information filtering system based on the Internet of things. In terms of hardware, the Internet of things is applied to capture network big data, and each module is designed according to the functionality, including data storage, distributed data filtering, user query processing, network big data capture and regional model construction, forming the overall hardware structure of the system;In terms of software, optimize the information filtering algorithm, denoise the big data of the Internet of things, cluster analyze the data category, calculate the distance between the data in the cluster and the cluster center, and filter the false and invalid data with large distance value. Grab the keyword data of social network software and set up comparative experiments. The results show that the system designed in this paper increases the amount of information filtering of network big data and improves the filtering accuracy and speed.
作者
李根
王瑞奇
李林
LI Gen;WANG Ruiqi;LI Lin(School of Artificial Intelligence and Big Data,Guangdong Polytechnic University of Business and Technology,Zhaoqing Guangdong 526000,China)
出处
《信息与电脑》
2022年第5期191-193,共3页
Information & Computer
关键词
物联网
网络大数据
信息过滤
internet of things
network big data
information filtering
