用习惯表达进行汉语情感分析

Yi-Jen Su, Huang-Wei Huang, Wu-Chih Hu
{"title":"用习惯表达进行汉语情感分析","authors":"Yi-Jen Su, Huang-Wei Huang, Wu-Chih Hu","doi":"10.1109/UMEDIA.2017.8074108","DOIUrl":null,"url":null,"abstract":"The rising of social media services causes Sentiment Analysis is becoming a critical research issue in recent years. Using the prediction of future opinion trends to adjust current business strategies is the most valuable application of emotion discovery. The major drawback of the previously proposed language model, CCLM, used to produce a larger number of terms in corpus causes the emotion classifier slowdown emotion judgement by spending too much time on searching. This research tried to improve the precision and performance of the emotion classifier, the idiomatic expression of human habit has been proposed to promote a novel sentence-level emotion classifier by using the Combined Jieba Customary Language Model (CJCLM). In the experiment, all Chinese sentences are retrieved from Plurk platform to present the improvement of the execution time by CJCLM.","PeriodicalId":440018,"journal":{"name":"2017 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using idiomatic expression for Chinese sentiment analysis\",\"authors\":\"Yi-Jen Su, Huang-Wei Huang, Wu-Chih Hu\",\"doi\":\"10.1109/UMEDIA.2017.8074108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rising of social media services causes Sentiment Analysis is becoming a critical research issue in recent years. Using the prediction of future opinion trends to adjust current business strategies is the most valuable application of emotion discovery. The major drawback of the previously proposed language model, CCLM, used to produce a larger number of terms in corpus causes the emotion classifier slowdown emotion judgement by spending too much time on searching. This research tried to improve the precision and performance of the emotion classifier, the idiomatic expression of human habit has been proposed to promote a novel sentence-level emotion classifier by using the Combined Jieba Customary Language Model (CJCLM). In the experiment, all Chinese sentences are retrieved from Plurk platform to present the improvement of the execution time by CJCLM.\",\"PeriodicalId\":440018,\"journal\":{\"name\":\"2017 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UMEDIA.2017.8074108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UMEDIA.2017.8074108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

随着社交媒体服务的兴起,情感分析成为近年来一个重要的研究课题。利用对未来舆论趋势的预测来调整当前的商业策略是情感发现最有价值的应用。先前提出的语言模型CCLM用于在语料库中产生大量术语,其主要缺点是情感分类器花费太多时间进行搜索,从而减缓了情感判断。本研究试图提高情感分类器的精度和性能,提出了一种基于人类习惯的习语表达方法,并利用结合Jieba习惯语言模型(Combined Jieba Customary Language Model, CJCLM)构建一种新的句子级情感分类器。在实验中,所有的中文句子都是从Plurk平台上检索的,以展示CJCLM对执行时间的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using idiomatic expression for Chinese sentiment analysis
The rising of social media services causes Sentiment Analysis is becoming a critical research issue in recent years. Using the prediction of future opinion trends to adjust current business strategies is the most valuable application of emotion discovery. The major drawback of the previously proposed language model, CCLM, used to produce a larger number of terms in corpus causes the emotion classifier slowdown emotion judgement by spending too much time on searching. This research tried to improve the precision and performance of the emotion classifier, the idiomatic expression of human habit has been proposed to promote a novel sentence-level emotion classifier by using the Combined Jieba Customary Language Model (CJCLM). In the experiment, all Chinese sentences are retrieved from Plurk platform to present the improvement of the execution time by CJCLM.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信