{"title":"基于词干的黏着性语言词性标注","authors":"Necva Bölücü, Burcu Can","doi":"10.1109/SIU.2017.7960386","DOIUrl":null,"url":null,"abstract":"Words are made up of morphemes being glued together in agglutinative languages. This makes it difficult to perform part-of-speech tagging for these languages due to sparsity. In this paper, we present two Hidden Markov Model based Bayesian PoS tagging models for agglutinative languages. Our first model is word-based and the second model is stem-based where the stems of the words are obtained from other two unsupervised stemmers: HPS stemmer and Morfessor FlatCat. The results show that stemming improves the accuracy in PoS tagging. We present the results for Turkish as an agglutinative language and English as a morphologically poor language.","PeriodicalId":217576,"journal":{"name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","volume":"1966 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Stem-based PoS tagging for agglutinative languages\",\"authors\":\"Necva Bölücü, Burcu Can\",\"doi\":\"10.1109/SIU.2017.7960386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Words are made up of morphemes being glued together in agglutinative languages. This makes it difficult to perform part-of-speech tagging for these languages due to sparsity. In this paper, we present two Hidden Markov Model based Bayesian PoS tagging models for agglutinative languages. Our first model is word-based and the second model is stem-based where the stems of the words are obtained from other two unsupervised stemmers: HPS stemmer and Morfessor FlatCat. The results show that stemming improves the accuracy in PoS tagging. We present the results for Turkish as an agglutinative language and English as a morphologically poor language.\",\"PeriodicalId\":217576,\"journal\":{\"name\":\"2017 25th Signal Processing and Communications Applications Conference (SIU)\",\"volume\":\"1966 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 25th Signal Processing and Communications Applications Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2017.7960386\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2017.7960386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stem-based PoS tagging for agglutinative languages
Words are made up of morphemes being glued together in agglutinative languages. This makes it difficult to perform part-of-speech tagging for these languages due to sparsity. In this paper, we present two Hidden Markov Model based Bayesian PoS tagging models for agglutinative languages. Our first model is word-based and the second model is stem-based where the stems of the words are obtained from other two unsupervised stemmers: HPS stemmer and Morfessor FlatCat. The results show that stemming improves the accuracy in PoS tagging. We present the results for Turkish as an agglutinative language and English as a morphologically poor language.
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