{"title":"利用用户生成的内容改进机器翻译","authors":"Atheer S. Al-Khalifa, Hend Suliman Al-Khalifa","doi":"10.1109/ICCITECHNOL.2011.5762660","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to overcome the limitation inherited in statistical machine translation services where the translation of new terms is not covered. The proposed approach is based on the power of user generated content to drive Arabic translations of English words. Our initial pilot experiment reveals the potential of our approach. This approach can act as an add-on to improve the quality of existing statistical translation services such as Google Translate.","PeriodicalId":211631,"journal":{"name":"2011 International Conference on Communications and Information Technology (ICCIT)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards improving machine translation using user generated content\",\"authors\":\"Atheer S. Al-Khalifa, Hend Suliman Al-Khalifa\",\"doi\":\"10.1109/ICCITECHNOL.2011.5762660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel approach to overcome the limitation inherited in statistical machine translation services where the translation of new terms is not covered. The proposed approach is based on the power of user generated content to drive Arabic translations of English words. Our initial pilot experiment reveals the potential of our approach. This approach can act as an add-on to improve the quality of existing statistical translation services such as Google Translate.\",\"PeriodicalId\":211631,\"journal\":{\"name\":\"2011 International Conference on Communications and Information Technology (ICCIT)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Communications and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCITECHNOL.2011.5762660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Communications and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHNOL.2011.5762660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards improving machine translation using user generated content
This paper presents a novel approach to overcome the limitation inherited in statistical machine translation services where the translation of new terms is not covered. The proposed approach is based on the power of user generated content to drive Arabic translations of English words. Our initial pilot experiment reveals the potential of our approach. This approach can act as an add-on to improve the quality of existing statistical translation services such as Google Translate.