{"title":"基于本体的在线消费者评论情感分类方法","authors":"J. Polpinij, A. Ghose","doi":"10.1109/WIIAT.2008.68","DOIUrl":null,"url":null,"abstract":"This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":"{\"title\":\"An Ontology-Based Sentiment Classification Methodology for Online Consumer Reviews\",\"authors\":\"J. Polpinij, A. Ghose\",\"doi\":\"10.1109/WIIAT.2008.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.\",\"PeriodicalId\":393772,\"journal\":{\"name\":\"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"63\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WIIAT.2008.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIIAT.2008.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Ontology-Based Sentiment Classification Methodology for Online Consumer Reviews
This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.