{"title":"自然语言处理的主题跟踪技术","authors":"K. Kaur","doi":"10.1145/2007052.2007066","DOIUrl":null,"url":null,"abstract":"Text mining is a field that automatically extracts previously unknown and useful information from unstructured textual data. It has strong connections with natural language processing. NLP has produced technologies that teach computers natural language so that they may analyze, understand and even generate text. Topic tracking is one of the technologies that has been developed and can be used in the text mining process. The main purpose of topic tracking is to identify and follow events presented in multiple news sources, including newswires, radio and TV broadcasts. It collects dispersed information together and makes it easy for user to get a general understanding. In this paper, a survey of recent topic tracking techniques is presented.","PeriodicalId":348804,"journal":{"name":"International Conference on Advances in Computing and Artificial Intelligence","volume":"72 8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Topic tracking techniques for natural language processing\",\"authors\":\"K. Kaur\",\"doi\":\"10.1145/2007052.2007066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Text mining is a field that automatically extracts previously unknown and useful information from unstructured textual data. It has strong connections with natural language processing. NLP has produced technologies that teach computers natural language so that they may analyze, understand and even generate text. Topic tracking is one of the technologies that has been developed and can be used in the text mining process. The main purpose of topic tracking is to identify and follow events presented in multiple news sources, including newswires, radio and TV broadcasts. It collects dispersed information together and makes it easy for user to get a general understanding. In this paper, a survey of recent topic tracking techniques is presented.\",\"PeriodicalId\":348804,\"journal\":{\"name\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"volume\":\"72 8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2007052.2007066\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Advances in Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2007052.2007066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Topic tracking techniques for natural language processing
Text mining is a field that automatically extracts previously unknown and useful information from unstructured textual data. It has strong connections with natural language processing. NLP has produced technologies that teach computers natural language so that they may analyze, understand and even generate text. Topic tracking is one of the technologies that has been developed and can be used in the text mining process. The main purpose of topic tracking is to identify and follow events presented in multiple news sources, including newswires, radio and TV broadcasts. It collects dispersed information together and makes it easy for user to get a general understanding. In this paper, a survey of recent topic tracking techniques is presented.