{"title":"数据","authors":"B. Ruddell","doi":"10.1017/9781108779678.008","DOIUrl":null,"url":null,"abstract":": [ Objective ] This paper analyzes the popular text similarity measures and discusses their latest developments. [ Coverage ] We retrieved 69 key articles from CNKI and Web of Science databases by searching “TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ” in Chinese and English respectively. [ Methods ] We systematically reviewed the text similarity measures focusing on their basic concepts, characteristics and future directions. [ Results ] There were four types of text similarity measures: String-based, Corpus-based, Knowledge-based and others. Measures based on the neural network, Knowledge-based measures and inter-disciplinary measures could be the future research directions. [ Limitations ] We did not discuss the applications of those measures. [ Conclusions ] This paper is a comprehensive review of text similarity measure research.","PeriodicalId":349969,"journal":{"name":"The Food-Energy-Water Nexus","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data\",\"authors\":\"B. Ruddell\",\"doi\":\"10.1017/9781108779678.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": [ Objective ] This paper analyzes the popular text similarity measures and discusses their latest developments. [ Coverage ] We retrieved 69 key articles from CNKI and Web of Science databases by searching “TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ” in Chinese and English respectively. [ Methods ] We systematically reviewed the text similarity measures focusing on their basic concepts, characteristics and future directions. [ Results ] There were four types of text similarity measures: String-based, Corpus-based, Knowledge-based and others. Measures based on the neural network, Knowledge-based measures and inter-disciplinary measures could be the future research directions. [ Limitations ] We did not discuss the applications of those measures. [ Conclusions ] This paper is a comprehensive review of text similarity measure research.\",\"PeriodicalId\":349969,\"journal\":{\"name\":\"The Food-Energy-Water Nexus\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Food-Energy-Water Nexus\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/9781108779678.008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Food-Energy-Water Nexus","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/9781108779678.008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
[目的]分析目前流行的文本相似度度量方法，并探讨其最新发展。【检索范围】我们分别通过中文和英文检索“TI:‘text similarity’or‘semantic similarity’or‘lexical similarity’”从CNKI和Web of Science数据库中检索到69篇关键文章。[方法]系统综述了文本相似度测度的基本概念、特点和发展方向。[结果]文本相似度度量有四种类型:基于字符串的、基于语料库的、基于知识的和其他。基于神经网络的测度、基于知识的测度和跨学科测度可能是未来的研究方向。[限制]我们没有讨论这些措施的应用。【结论】本文对文本相似度测度研究进行了较为全面的综述。
: [ Objective ] This paper analyzes the popular text similarity measures and discusses their latest developments. [ Coverage ] We retrieved 69 key articles from CNKI and Web of Science databases by searching “TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ” in Chinese and English respectively. [ Methods ] We systematically reviewed the text similarity measures focusing on their basic concepts, characteristics and future directions. [ Results ] There were four types of text similarity measures: String-based, Corpus-based, Knowledge-based and others. Measures based on the neural network, Knowledge-based measures and inter-disciplinary measures could be the future research directions. [ Limitations ] We did not discuss the applications of those measures. [ Conclusions ] This paper is a comprehensive review of text similarity measure research.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
