{"title":"学习巴西葡萄牙语减句规则","authors":"Daniel Kawamoto, T. Pardo","doi":"10.5220/0003030300900099","DOIUrl":null,"url":null,"abstract":"We present in this paper a method for sentence reduction with summarization purposes. The task is modeled as a machine learning problem, relying on shallow and linguistic features, in order to automatically learn symbolic patterns/rules that produce good sentence reductions. We evaluate our results with Brazilian Portuguese texts and show that we achieve high accuracy and produce better results than the existing solution for this language.","PeriodicalId":378427,"journal":{"name":"International Workshop on Natural Language Processing and Cognitive Science","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Learning Sentence Reduction Rules for Brazilian Portuguese\",\"authors\":\"Daniel Kawamoto, T. Pardo\",\"doi\":\"10.5220/0003030300900099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present in this paper a method for sentence reduction with summarization purposes. The task is modeled as a machine learning problem, relying on shallow and linguistic features, in order to automatically learn symbolic patterns/rules that produce good sentence reductions. We evaluate our results with Brazilian Portuguese texts and show that we achieve high accuracy and produce better results than the existing solution for this language.\",\"PeriodicalId\":378427,\"journal\":{\"name\":\"International Workshop on Natural Language Processing and Cognitive Science\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Natural Language Processing and Cognitive Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0003030300900099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Natural Language Processing and Cognitive Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0003030300900099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning Sentence Reduction Rules for Brazilian Portuguese
We present in this paper a method for sentence reduction with summarization purposes. The task is modeled as a machine learning problem, relying on shallow and linguistic features, in order to automatically learn symbolic patterns/rules that produce good sentence reductions. We evaluate our results with Brazilian Portuguese texts and show that we achieve high accuracy and produce better results than the existing solution for this language.
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