Neha Prabhugaonkar, Sai Kiran Peketi, Kavita Ganeshan, U. Sureshkumar
{"title":"区分代码借用与代码混合","authors":"Neha Prabhugaonkar, Sai Kiran Peketi, Kavita Ganeshan, U. Sureshkumar","doi":"10.1145/3041823.3067692","DOIUrl":null,"url":null,"abstract":"In linguistics, Code-Switching and Code-Borrowing are two separate concepts and identifying them is a challenging task. The social media dataset for the challenge [1] consists of English-Hindi tweets. We have designed an ensemble model for the challenge to identify and rank the borrowed words.","PeriodicalId":173593,"journal":{"name":"Proceedings of the 4th ACM IKDD Conferences on Data Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differentiating Code-Borrowing from Code-Mixing\",\"authors\":\"Neha Prabhugaonkar, Sai Kiran Peketi, Kavita Ganeshan, U. Sureshkumar\",\"doi\":\"10.1145/3041823.3067692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In linguistics, Code-Switching and Code-Borrowing are two separate concepts and identifying them is a challenging task. The social media dataset for the challenge [1] consists of English-Hindi tweets. We have designed an ensemble model for the challenge to identify and rank the borrowed words.\",\"PeriodicalId\":173593,\"journal\":{\"name\":\"Proceedings of the 4th ACM IKDD Conferences on Data Sciences\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th ACM IKDD Conferences on Data Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3041823.3067692\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th ACM IKDD Conferences on Data Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3041823.3067692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In linguistics, Code-Switching and Code-Borrowing are two separate concepts and identifying them is a challenging task. The social media dataset for the challenge [1] consists of English-Hindi tweets. We have designed an ensemble model for the challenge to identify and rank the borrowed words.