{"title":"基于语义关系分析的情感分析模型研究","authors":"T. K. Tran, T. Phan","doi":"10.4018/IJSE.2018070104","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an effective model for aspect-based sentiment analysis. First, we combined a sentiment dictionary and syntactic dependency rules to extract reliable word pairs (sentiment — aspect). Then, thanks to ontology, we grouped those aspects and determined the sentiment polarity of each. When we conducted experiments on real reviews, the system showed positive results.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Towards a Sentiment Analysis Model Based on Semantic Relation Analysis\",\"authors\":\"T. K. Tran, T. Phan\",\"doi\":\"10.4018/IJSE.2018070104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an effective model for aspect-based sentiment analysis. First, we combined a sentiment dictionary and syntactic dependency rules to extract reliable word pairs (sentiment — aspect). Then, thanks to ontology, we grouped those aspects and determined the sentiment polarity of each. When we conducted experiments on real reviews, the system showed positive results.\",\"PeriodicalId\":272943,\"journal\":{\"name\":\"Int. J. Synth. Emot.\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Synth. Emot.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJSE.2018070104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Synth. Emot.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJSE.2018070104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a Sentiment Analysis Model Based on Semantic Relation Analysis
In this paper, we propose an effective model for aspect-based sentiment analysis. First, we combined a sentiment dictionary and syntactic dependency rules to extract reliable word pairs (sentiment — aspect). Then, thanks to ontology, we grouped those aspects and determined the sentiment polarity of each. When we conducted experiments on real reviews, the system showed positive results.