{"title":"基于twitter的事件检测与分析系统","authors":"Rui Li, Kin Hou Lei, Ravi V. Khadiwala, K. Chang","doi":"10.1109/ICDE.2012.125","DOIUrl":null,"url":null,"abstract":"Witnessing the emergence of Twitter, we propose a Twitter-based Event Detection and Analysis System (TEDAS), which helps to (1) detect new events, to (2) analyze the spatial and temporal pattern of an event, and to (3) identify importance of events. In this demonstration, we show the overall system architecture, explain in detail the implementation of the components that crawl, classify, and rank tweets and extract location from tweets, and present some interesting results of our system.","PeriodicalId":321608,"journal":{"name":"2012 IEEE 28th International Conference on Data Engineering","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"462","resultStr":"{\"title\":\"TEDAS: A Twitter-based Event Detection and Analysis System\",\"authors\":\"Rui Li, Kin Hou Lei, Ravi V. Khadiwala, K. Chang\",\"doi\":\"10.1109/ICDE.2012.125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Witnessing the emergence of Twitter, we propose a Twitter-based Event Detection and Analysis System (TEDAS), which helps to (1) detect new events, to (2) analyze the spatial and temporal pattern of an event, and to (3) identify importance of events. In this demonstration, we show the overall system architecture, explain in detail the implementation of the components that crawl, classify, and rank tweets and extract location from tweets, and present some interesting results of our system.\",\"PeriodicalId\":321608,\"journal\":{\"name\":\"2012 IEEE 28th International Conference on Data Engineering\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"462\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 28th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2012.125\",\"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 IEEE 28th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2012.125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TEDAS: A Twitter-based Event Detection and Analysis System
Witnessing the emergence of Twitter, we propose a Twitter-based Event Detection and Analysis System (TEDAS), which helps to (1) detect new events, to (2) analyze the spatial and temporal pattern of an event, and to (3) identify importance of events. In this demonstration, we show the overall system architecture, explain in detail the implementation of the components that crawl, classify, and rank tweets and extract location from tweets, and present some interesting results of our system.
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