{"title":"葡萄牙语隐含词自动识别的学习规则","authors":"M. Machado, T. Pardo, E. Ruiz, Ariani Di Felippo","doi":"10.5753/stil.2021.17787","DOIUrl":null,"url":null,"abstract":"This sentiment analysis work is focused on the task of identifying aspects, emphasizing the so-called implicit aspects, i.e., those that are not explicitly mentioned in the texts. For this, we analyzed frequency-based methods, adapted rules from the English language to Portuguese, and developed a method that learns new rules through corpus analysis.","PeriodicalId":194867,"journal":{"name":"Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL 2021)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Learning rules for automatic identification of implicit aspects in Portuguese\",\"authors\":\"M. Machado, T. Pardo, E. Ruiz, Ariani Di Felippo\",\"doi\":\"10.5753/stil.2021.17787\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This sentiment analysis work is focused on the task of identifying aspects, emphasizing the so-called implicit aspects, i.e., those that are not explicitly mentioned in the texts. For this, we analyzed frequency-based methods, adapted rules from the English language to Portuguese, and developed a method that learns new rules through corpus analysis.\",\"PeriodicalId\":194867,\"journal\":{\"name\":\"Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL 2021)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL 2021)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5753/stil.2021.17787\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/stil.2021.17787","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning rules for automatic identification of implicit aspects in Portuguese
This sentiment analysis work is focused on the task of identifying aspects, emphasizing the so-called implicit aspects, i.e., those that are not explicitly mentioned in the texts. For this, we analyzed frequency-based methods, adapted rules from the English language to Portuguese, and developed a method that learns new rules through corpus analysis.