Topic Detection and Tracking Pilot Study Final Report
Topic Detection and Tracking Pilot Study Final Report
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DOI：
10.1184/r1/6626252.v1
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
James Allan;J. Carbonell;G. Doddington;J. Yamron;Yiming Yang
中科院分区：
文献类型：
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作者：
James Allan;J. Carbonell;G. Doddington;J. Yamron;Yiming Yang
主题检测和跟踪（TDT）是DARPA发起的一项倡议，旨在调查在广播新闻故事流中发现和跟踪新事件的最新技术水平。TDT问题由三个主要任务组成：（1）将数据流，特别是已识别的语音，分割成不同的故事;（2）识别那些首先讨论新闻中发生的新事件的新闻故事;（3）给定少量关于事件的新闻故事样本，在流中找到所有后续故事。
Topic Detection and Tracking (TDT) is a DARPA-sponsored initiative to investigate the state of the art in finding and following new events in a stream of broadcast news stories. The TDT problem consists of three major tasks: (1) segmenting a stream of data, especially recognized speech, into distinct stories; (2) identifying those news stories that are the first to discuss a new event occurring in the news; and (3) given a small number of sample news stories about an event, finding all following stories in the stream.