The Today Tendency of Sentiment Classification

V. Phu, Vo Thi Ngoc Tran
{"title":"The Today Tendency of Sentiment Classification","authors":"V. Phu, Vo Thi Ngoc Tran","doi":"10.5772/INTECHOPEN.74930","DOIUrl":null,"url":null,"abstract":"Sentiment classification has already been studied for many years because it has had many crucial contributions to many different fields in everyday life, such as in political activi -ties, commodity production, and commercial activities. There have been many kinds of the sentiment analysis such as machine learning approaches, lexicon-based approaches, etc., for many years. The today tendency of the sentiment classification is as follows: (1) Processing many big data sets with shortening execution times (2) Having a high accuracy (3) Integrating flexibly and easily into many small machines or many different approaches. We will present each category in more details.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"84 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence - Emerging Trends and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.74930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Sentiment classification has already been studied for many years because it has had many crucial contributions to many different fields in everyday life, such as in political activi -ties, commodity production, and commercial activities. There have been many kinds of the sentiment analysis such as machine learning approaches, lexicon-based approaches, etc., for many years. The today tendency of the sentiment classification is as follows: (1) Processing many big data sets with shortening execution times (2) Having a high accuracy (3) Integrating flexibly and easily into many small machines or many different approaches. We will present each category in more details.
情感分类的今天趋势
情感分类已经被研究了很多年,因为它在日常生活的许多不同领域,如政治活动、商品生产和商业活动中都有许多重要的贡献。多年来,情感分析的方法有很多种,如机器学习方法、基于词典的方法等。当今情感分类的趋势是:(1)处理大量大数据集,缩短执行时间;(2)具有较高的准确性;(3)灵活、容易地集成到许多小型机器或许多不同的方法中。我们将更详细地介绍每一类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信