摘要
为提高游客在互联网旅游服务平台上评论数据分析的准确度,提出一种基于机器学习分类方法的数据智能分析技术。利用成熟的自动抓取等软件技术,从某旅游网络平台上抓取了游客的初始评论数据,同时设置了相应的训练集与测试集,完成了评论数据的文本清理、词性标注与人工分类等预处理操作。在此基础上,通过引入支持向量机等机器学习的分类方法,实现待处理评论数据的智能分类与分析,从而进一步改进游客情感数据挖掘的准确度,优化旅游目的地的顾客体验。数据测试仿真结果表明,与语义分析方法相比,基于机器学习方法的智能分析技术具有更高的数据分析准确度。
In order to improve the accuracy of data analysis of tourists’comments on the internet tourism service platform,an intelligent data analysis technology based on machine learning classification method is proposed.By using the mature software technology such as automatic grabbing,grabs the initial comment data of tourists from a tourism network platform,sets up the corresponding training set and test set,and completes the text cleaning,part of speech tagging and manual classification of the comment data.On this basis,by introducing the classification methods of machine learning such as support vector machine,the intelligent classification and analysis of the comment data to be processed can be realized,so as to further improve the accuracy of the emotional data mining of tourists and optimize the customer experience of tourist destinations.The simulation results of data test show that compared with semantic analysis method,the intelligent analysis technology based on machine learning method has higher data analysis accuracy.
作者
马骞
MA Qian(Xi'an Vocational and Technical College of Aeronautics and Astronautics,Xi'an 710089,China)
出处
《电子设计工程》
2021年第12期48-51,56,共5页
Electronic Design Engineering
基金
陕西省教育科学规划课题(SGH17V012)
西安航空职业技术学院科研计划项目(19XHSK-015)。
关键词
数据分析
机器学习
支持向量机
中文语料
特征提取
文本分类
data analysis
machine learning
support vector machine
Chinese corpus
feature extraction
text classification
