物联网环境下的深度学习文本分类算法的研究与实践  

Research and practice on deep learning text classification algorithm in Internet of Things environment

作　　者：宋丹 SONG Dan(Ma̓anshan University,Ma̓anshan,Anhui 243000,China)

机构地区：[1]马鞍山学院,安徽马鞍山243000

出　　处：《计算机应用文摘》2024年第16期90-92,共3页Chinese Journal of Computer Application

摘　　要：通过将各种智能设备连接在一起,物联网技术实现了对数据的实时采集、传输和处理。这个过程中产生了大量蕴含丰富信息的文本数据(如设备的日志信息、用户的反馈意见),它们对设备的状态监测、故障预警、用户行为分析等具有重要意义。然而,由于物联网环境下文本数据的海量性、多样性和实时性,传统文本分类方法难以满足需求。因此,文章提出了一种基于深度学习的文本分类算法,旨在解决物联网环境下文本分类的难题。By connecting various smart devices together,the Internet of Things technology enables the realtime acquisition,transmission and processing of data.In this process,a large amount of text data containing rich information(such as device log information and user feedback)is generated,which is of great significance for device status monitoring,fault warning,and user behavior analysis.However,due to the massive,diverse and real-time text data in the Internet of Things environment,traditional text classification methods are difficult to meet the needs.Therefore,this paper proposes a text classification algorithm based on deep learning to solve the problem of text classification in the Internet of Things environment.

关 键 词：物联网 深度学习 文本分类 词向量 卷积神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]