{"title":"科技文章不同章节词汇束的典型性","authors":"Haotong Wang, Y. Lepage, Chooi-Ling Goh","doi":"10.1145/3421515.3421517","DOIUrl":null,"url":null,"abstract":"This paper proposes a method to quantify the typicality of lexical bundles in sections of academic articles, specifically in the field of Natural Language Processing papers. Typicality is defined as the product of individual KL-divergence scores and the probability of a bundle to appear in a type of section. An evaluation of our typicality measure against two other baselines shows slight improvements according to the Silhouette coefficient.","PeriodicalId":294293,"journal":{"name":"2020 2nd Symposium on Signal Processing Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Typicality of Lexical Bundles in Different Sections of Scientific Articles\",\"authors\":\"Haotong Wang, Y. Lepage, Chooi-Ling Goh\",\"doi\":\"10.1145/3421515.3421517\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a method to quantify the typicality of lexical bundles in sections of academic articles, specifically in the field of Natural Language Processing papers. Typicality is defined as the product of individual KL-divergence scores and the probability of a bundle to appear in a type of section. An evaluation of our typicality measure against two other baselines shows slight improvements according to the Silhouette coefficient.\",\"PeriodicalId\":294293,\"journal\":{\"name\":\"2020 2nd Symposium on Signal Processing Systems\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd Symposium on Signal Processing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3421515.3421517\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd Symposium on Signal Processing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3421515.3421517","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Typicality of Lexical Bundles in Different Sections of Scientific Articles
This paper proposes a method to quantify the typicality of lexical bundles in sections of academic articles, specifically in the field of Natural Language Processing papers. Typicality is defined as the product of individual KL-divergence scores and the probability of a bundle to appear in a type of section. An evaluation of our typicality measure against two other baselines shows slight improvements according to the Silhouette coefficient.
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