Topic Detection and Tracking Pilot Study Final Report Export

@inproceedings{citeulike:3576190, abstract = {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. The TDT Pilot Study ran from September 1996 through October 1997. The primary participants were DARPA, Carnegie Mellon University, Dragon Systems, and the University of Massachusetts at Amherst. This report summarizes the findings of the pilot study. The TDT work continues in a new project involving larger training and test corpora, more active participants, and a more broadly defined notion of \&\#034;topic\&\#034; than was used in the pilot study. The following individuals partici...}, author = {Allan, James and Carbonell, Jaime and Doddington, George and Yamron, Jonathan and Yang, Yiming and Umass, James A. and Cmu, Brian A. and Cmu, Doug B. and Cmu, Adam B. and Cmu, Ralf B. and Dragon, Ira C. and Darpa, George D. and Cmu, Alex H. and Cmu, John L. and Umass, Victor L. and Cmu, Xin L. and Dragon, Steve L. and Van Mulbregt Dragon and Umass, Ron P. and Cmu, Thomas P. and Umass, Jay P. and Umass, Mike S.}, booktitle = {In Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop}, citeulike-article-id = {3576190}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.6373}, keywords = {text-mining, topic-detection-and-tracking}, pages = {194--218}, posted-at = {2008-11-19 03:25:00}, priority = {2}, title = {Topic Detection and Tracking Pilot Study Final Report}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.6373}, year = {1998} }

TY - CONF ID - citeulike:3576190 L3 - citeulike-article-id:3576190 N2 - 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. The TDT Pilot Study ran from September 1996 through October 1997. The primary participants were DARPA, Carnegie Mellon University, Dragon Systems, and the University of Massachusetts at Amherst. This report summarizes the findings of the pilot study. The TDT work continues in a new project involving larger training and test corpora, more active participants, and a more broadly defined notion of "topic" than was used in the pilot study. The following individuals partici... EP - 218 TI - Topic Detection and Tracking Pilot Study Final Report T2 - In Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop SP - 194 KW - text-mining KW - topic-detection-and-tracking AU - Allan, James AU - Carbonell, Jaime AU - Doddington, George AU - Yamron, Jonathan AU - Yang, Yiming AU - Umass, James AU - Cmu, Brian AU - Cmu, Doug AU - Cmu, Adam AU - Cmu, Ralf AU - Dragon, Ira AU - Darpa, George AU - Cmu, Alex AU - Cmu, John AU - Umass, Victor AU - Cmu, Xin AU - Dragon, Steve AU - Van Mulbregt Dragon AU - Umass, Ron AU - Cmu, Thomas AU - Umass, Jay AU - Umass, Mike PY - 1998/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.6373 ER -