摘要
随着在线视频的大量增长,越来越多的人开始在视频网站上发表对视频的评论。这些评论通常会带有用户的个人情感色彩和视频中的一些关键信息,从而对网络用户的视频观看决策有重要影响。如何自动地对在线视频评论进行情感分类和关键词提取,已成为目前亟待解决的问题。文章重点研究在线视频评论的情感分类技术,分析了不同特征提取和特征选择方法以及不同分类算法对在线视频评论情感分类精度的影响。仿真实验表明,文章提出的在线视频评论情感分类模型具有较高的准确性。
With the rapid growth of online videos, more and more people begin to publish comments on videos of video websites. Users* comments usually include personal emotions and some of the key information about the videos, which makes significant impact on video viewing decisions for Web users. Emotion classification and extracting key words from online video comments automatically have become an urgent problem. This paper focuses on the emotion classification for online video comments, and analyzes the influence of different feature extraction and feature selection methods and different classification algorithms on the accuracy of online video comments emotion classification. Simulation results show that the online video comments emotion classification model proposed in this paper has high accuracy.
作者
李辉
倪时策
肖佳
赵天忠
LI Hui;NI Shice;XIAO Jia;ZHAO Tianzhong(Shanghai Huawei Technology Co. Ltd., Shanghai 201206, China;Investigation Technology Center, PLCMC, Beijing 100120, China;State Key Laboratory of Networking and Switching, Beijing University of Posts and Telecommunications, Beijing 100876, China;PLA 78156, Haidong Qinghai 810800, China)
出处
《信息网络安全》
CSCD
北大核心
2019年第5期61-68,共8页
Netinfo Security
基金
国家242信息安全专项[2018A094]
关键词
情感分类
分类算法
特征提取
特征选择
emotion classification
classification algorithm
feature extraction
feature selection
