{"title":"高校应急语料库建设研究","authors":"Lu Qian, Zhao Xiaobing","doi":"10.1109/ICINIS.2012.43","DOIUrl":null,"url":null,"abstract":"Recently, emergency early warning is a popular research area, the purpose of which is to prevent outbreak of the events endangering social stability. To establish the corpus of university emergency is the first step of the research. The paper discusses the current situation of the corpus. Then, we give the classification system of the university emergency. In the paper, we propose the basic framework of technology route how to build the corpus. At the same time, we study the key technologies about construction of this corpus, namely, text collection, word segmentation, named entity labeling and chunks labeling. Based on the corpus we will explore university emergency detection and event content extraction in the future.","PeriodicalId":302503,"journal":{"name":"2012 Fifth International Conference on Intelligent Networks and Intelligent Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study on the Construction of Corpus of University Emergency\",\"authors\":\"Lu Qian, Zhao Xiaobing\",\"doi\":\"10.1109/ICINIS.2012.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, emergency early warning is a popular research area, the purpose of which is to prevent outbreak of the events endangering social stability. To establish the corpus of university emergency is the first step of the research. The paper discusses the current situation of the corpus. Then, we give the classification system of the university emergency. In the paper, we propose the basic framework of technology route how to build the corpus. At the same time, we study the key technologies about construction of this corpus, namely, text collection, word segmentation, named entity labeling and chunks labeling. Based on the corpus we will explore university emergency detection and event content extraction in the future.\",\"PeriodicalId\":302503,\"journal\":{\"name\":\"2012 Fifth International Conference on Intelligent Networks and Intelligent Systems\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth International Conference on Intelligent Networks and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINIS.2012.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fifth International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2012.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on the Construction of Corpus of University Emergency
Recently, emergency early warning is a popular research area, the purpose of which is to prevent outbreak of the events endangering social stability. To establish the corpus of university emergency is the first step of the research. The paper discusses the current situation of the corpus. Then, we give the classification system of the university emergency. In the paper, we propose the basic framework of technology route how to build the corpus. At the same time, we study the key technologies about construction of this corpus, namely, text collection, word segmentation, named entity labeling and chunks labeling. Based on the corpus we will explore university emergency detection and event content extraction in the future.