{"title":"利用频繁子树挖掘方法对树库进行定量分析","authors":"S. Martens","doi":"10.3115/1708124.1708140","DOIUrl":null,"url":null,"abstract":"The first task of statistical computational linguistics, or any other type of data-driven processing of language, is the extraction of counts and distributions of phenomena. This is much more difficult for the type of complex structured data found in treebanks and in corpora with sophisticated annotation than for tokenized texts. Recent developments in data mining, particularly in the extraction of frequent subtrees from treebanks, offer some solutions. We have applied a modified version of the TreeMiner algorithm to a small treebank and present some promising results.","PeriodicalId":359354,"journal":{"name":"Workshop on Graph-based Methods for Natural Language Processing","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Quantitative analysis of treebanks using frequent subtree mining methods\",\"authors\":\"S. Martens\",\"doi\":\"10.3115/1708124.1708140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The first task of statistical computational linguistics, or any other type of data-driven processing of language, is the extraction of counts and distributions of phenomena. This is much more difficult for the type of complex structured data found in treebanks and in corpora with sophisticated annotation than for tokenized texts. Recent developments in data mining, particularly in the extraction of frequent subtrees from treebanks, offer some solutions. We have applied a modified version of the TreeMiner algorithm to a small treebank and present some promising results.\",\"PeriodicalId\":359354,\"journal\":{\"name\":\"Workshop on Graph-based Methods for Natural Language Processing\",\"volume\":\"192 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Graph-based Methods for Natural Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1708124.1708140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Graph-based Methods for Natural Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1708124.1708140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantitative analysis of treebanks using frequent subtree mining methods
The first task of statistical computational linguistics, or any other type of data-driven processing of language, is the extraction of counts and distributions of phenomena. This is much more difficult for the type of complex structured data found in treebanks and in corpora with sophisticated annotation than for tokenized texts. Recent developments in data mining, particularly in the extraction of frequent subtrees from treebanks, offer some solutions. We have applied a modified version of the TreeMiner algorithm to a small treebank and present some promising results.