{"title":"使用机器学习技术进行情感分析的统计特征识别","authors":"A. Kamal, M. Abulaish","doi":"10.1109/ISCBI.2013.43","DOIUrl":null,"url":null,"abstract":"Due to increasing fascinating trend of using internet and online social media, user-generated contents are growing exponentially on the Web, containing users' opinion on various products. In this paper, we have proposed a sentiment analysis system which combines rule-based and machine learning approaches to identify feature-opinion pairs and their polarity. The efficiency of the proposed system is established through experimentation over customer reviews on different electronic products.","PeriodicalId":311471,"journal":{"name":"2013 International Symposium on Computational and Business Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Statistical Features Identification for Sentiment Analysis Using Machine Learning Techniques\",\"authors\":\"A. Kamal, M. Abulaish\",\"doi\":\"10.1109/ISCBI.2013.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to increasing fascinating trend of using internet and online social media, user-generated contents are growing exponentially on the Web, containing users' opinion on various products. In this paper, we have proposed a sentiment analysis system which combines rule-based and machine learning approaches to identify feature-opinion pairs and their polarity. The efficiency of the proposed system is established through experimentation over customer reviews on different electronic products.\",\"PeriodicalId\":311471,\"journal\":{\"name\":\"2013 International Symposium on Computational and Business Intelligence\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Symposium on Computational and Business Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCBI.2013.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Symposium on Computational and Business Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCBI.2013.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Features Identification for Sentiment Analysis Using Machine Learning Techniques
Due to increasing fascinating trend of using internet and online social media, user-generated contents are growing exponentially on the Web, containing users' opinion on various products. In this paper, we have proposed a sentiment analysis system which combines rule-based and machine learning approaches to identify feature-opinion pairs and their polarity. The efficiency of the proposed system is established through experimentation over customer reviews on different electronic products.