波斯语中基于方面的无监督情感分析:方面的提取和聚类

Reza Akhoundzade, Kourosh Hashemi Devin
{"title":"波斯语中基于方面的无监督情感分析:方面的提取和聚类","authors":"Reza Akhoundzade, Kourosh Hashemi Devin","doi":"10.1109/ICCKE50421.2020.9303651","DOIUrl":null,"url":null,"abstract":"Sentiment analysis is the field of natural language processing to analyze user feedback, preferences, and evaluations from the text. Different organizations in most social scopes use this context as an appropriate tool to find their strengths and weaknesses. In this field of research, the objective is to determine the positive or negative orientations of users towards the features of a product or commodity. Solving this problem consists of two main steps: aspect extraction and identifying the positive or negative tendencies of users towards those aspects. Two of the most critical issues of sentiment analysis in the Persian language are the lack of comprehensive labeled data and the significant difference between colloquial and formal sentences in Persian. One of the most important methods to confront the first problem is to apply unsupervised methods. In this research, a system for aspect-based sentiment analysis in the Persian language is proposed using unsupervised methods. The Sentiment words extraction step is done in another article [1]. The aspect extraction and clustering steps are done using topic modeling methods and neural networks and taking benefit of rule-based methods. This system has been evaluated using precision and recall criteria. The F1 criterion for extracting aspect words in the proposed system was 0.766.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Unsupervised aspect-based Sentiment Analysis in the Persian language: Extracting and clustering aspects\",\"authors\":\"Reza Akhoundzade, Kourosh Hashemi Devin\",\"doi\":\"10.1109/ICCKE50421.2020.9303651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentiment analysis is the field of natural language processing to analyze user feedback, preferences, and evaluations from the text. Different organizations in most social scopes use this context as an appropriate tool to find their strengths and weaknesses. In this field of research, the objective is to determine the positive or negative orientations of users towards the features of a product or commodity. Solving this problem consists of two main steps: aspect extraction and identifying the positive or negative tendencies of users towards those aspects. Two of the most critical issues of sentiment analysis in the Persian language are the lack of comprehensive labeled data and the significant difference between colloquial and formal sentences in Persian. One of the most important methods to confront the first problem is to apply unsupervised methods. In this research, a system for aspect-based sentiment analysis in the Persian language is proposed using unsupervised methods. The Sentiment words extraction step is done in another article [1]. The aspect extraction and clustering steps are done using topic modeling methods and neural networks and taking benefit of rule-based methods. This system has been evaluated using precision and recall criteria. The F1 criterion for extracting aspect words in the proposed system was 0.766.\",\"PeriodicalId\":402043,\"journal\":{\"name\":\"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE50421.2020.9303651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE50421.2020.9303651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

情感分析是自然语言处理的领域,用于分析文本中的用户反馈、偏好和评价。大多数社会范围内的不同组织都将此上下文作为发现其优势和劣势的适当工具。在这一研究领域,目标是确定用户对产品或商品特征的积极或消极倾向。解决这个问题包括两个主要步骤:方面提取和识别用户对这些方面的积极或消极倾向。波斯语情感分析的两个最关键的问题是缺乏全面的标记数据和波斯语口语和正式句之间的显着差异。解决第一个问题的最重要的方法之一是应用无监督方法。在这项研究中,提出了一个基于方面的波斯语情感分析系统,该系统采用无监督方法。情感词提取步骤在另一篇文章[1]中完成。利用主题建模方法和神经网络,利用基于规则的方法完成方面的提取和聚类步骤。该系统已使用精度和召回标准进行了评估。在该系统中提取方面词的F1准则为0.766。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unsupervised aspect-based Sentiment Analysis in the Persian language: Extracting and clustering aspects
Sentiment analysis is the field of natural language processing to analyze user feedback, preferences, and evaluations from the text. Different organizations in most social scopes use this context as an appropriate tool to find their strengths and weaknesses. In this field of research, the objective is to determine the positive or negative orientations of users towards the features of a product or commodity. Solving this problem consists of two main steps: aspect extraction and identifying the positive or negative tendencies of users towards those aspects. Two of the most critical issues of sentiment analysis in the Persian language are the lack of comprehensive labeled data and the significant difference between colloquial and formal sentences in Persian. One of the most important methods to confront the first problem is to apply unsupervised methods. In this research, a system for aspect-based sentiment analysis in the Persian language is proposed using unsupervised methods. The Sentiment words extraction step is done in another article [1]. The aspect extraction and clustering steps are done using topic modeling methods and neural networks and taking benefit of rule-based methods. This system has been evaluated using precision and recall criteria. The F1 criterion for extracting aspect words in the proposed system was 0.766.
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