{"title":"阿法安形态根鉴别的概率与分组方法","authors":"Getachew Mamo Wegari, M. Melucci, S. Teferra","doi":"10.1109/CONFLUENCE.2016.7508039","DOIUrl":null,"url":null,"abstract":"Morphological models are used in many natural language processing tasks including machine translation and speech recognition. We investigated probabilistic and grouping methods to develop a morphological root identification model for Afaan Oromo. In this paper, we have experimentally shown that the proposed methods can improve the morphological root identification performance of some state-of-the-art methods.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Probabilistic and grouping methods for morphological root identification for Afaan Oromo\",\"authors\":\"Getachew Mamo Wegari, M. Melucci, S. Teferra\",\"doi\":\"10.1109/CONFLUENCE.2016.7508039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Morphological models are used in many natural language processing tasks including machine translation and speech recognition. We investigated probabilistic and grouping methods to develop a morphological root identification model for Afaan Oromo. In this paper, we have experimentally shown that the proposed methods can improve the morphological root identification performance of some state-of-the-art methods.\",\"PeriodicalId\":299044,\"journal\":{\"name\":\"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONFLUENCE.2016.7508039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONFLUENCE.2016.7508039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic and grouping methods for morphological root identification for Afaan Oromo
Morphological models are used in many natural language processing tasks including machine translation and speech recognition. We investigated probabilistic and grouping methods to develop a morphological root identification model for Afaan Oromo. In this paper, we have experimentally shown that the proposed methods can improve the morphological root identification performance of some state-of-the-art methods.