tdt.bib

@INPROCEEDINGS{allan98topic,
  AUTHOR = {James Allan and Jaime Carbonell and George Doddington and Jonathan Yamron and Yiming Yang},
  TITLE = {Topic Detection and Tracking Pilot Study Final Report},
  BOOKTITLE = {Proc. DARPA Broadcast News Transcription and Understanding Workshop},
  MONTH = {February},
  YEAR = {1998},
  URL = {http://www-ciir.cs.umass.edu/~allan/Papers/bntuw98.ps},
  ANNOTE = {A compilation of the previous results of CMU, UMASS and Dragon Systems in the area of Topic Detection and Tracking.}
}

@INPROCEEDINGS{allan00,
  AUTHOR = {James Allan and Victor Lavrenko and H Jin},
  TITLE = {First Story Detection in TDT in Hard},
  BOOKTITLE = {Proc. 9th Conference on Information Knowledge Management CIKM},
  YEAR = {2000},
  PAGES = {374--381},
  ADDRESS = {McClean, VA USA},
  URL = {},
  ANNOTE = {The authors reduce the first story problem to TDT tracking problem. They are quite pessimistic about improvement in tracking by adjusting parameters.}
}

@INPROCEEDINGS{allan98online,
  AUTHOR = {James Allan and Ron Papka and Victor Lavrenko},
  TITLE = {On-line New Event Detection and Tracking},
  BOOKTITLE = {Proc. ACM SIGIR},
  PAGES = {37--45},
  YEAR = {1998},
  URL = {http://www-ciir.cs.umass.edu/\~allan/Papers/sigir98.ps},
  ANNOTE = {The paper introduces a modified 'single-pass' clustering method for first story detection. Some techniques for topic tracking are also presented (monitoring the occurrence of surprising vocabulary, using common words and adaptation}
}

@TECHREPORT{allan98,
  AUTHOR = {James Alla and Victor Lavrenko and Ron Papka},
  TITLE = {Event Tracking},
  INSTITUTION = {Department of Computer Science, University of Massachusetts},
  NUMBER = {CIIR Technical Report IR -- 128},
  YEAR = {1998},
  ANNOTE = {The anatomy and results of event tracking project outcome in UMass.}
}

@INPROCEEDINGS{carthy00,
  AUTHOR = {Joe Carthy and Alan Smeaton},
  TITLE = {The Design of a Topic Tracking System},
  BOOKTITLE = {Proc. 22nd Annual Colloquim on Information Retrieval Reseach},
  ADDRESS = {Cambridge, UK},
  YEAR = {2000},
  ANNOTE = {The authors present two topic tracking systems. The first employs 'traditional' information retrieval methods (comparison of term vectors), while the second adopts lexical chaining. The paper seems quite slim in content.}
}

@PHDTHESIS{papka99,
  AUTHOR = {Ron Papka},
  TITLE = {On-line New Event Detection, Clustering and Tracking},
  SCHOOL = {Department of Computer Science, University of Massachusetts},
  YEAR = {1999},
  URL = {http://cobar.cs.umass.edu/pubfiles/ir-179.ps.gz},
  ANNOTE = {The thesis portrays the problems regarding the processing of on-line text material, such as newsfeed. He examines the clustering thresholds quite throughly. This publication pretty much sums up the works of Papka as to TDT problems.}
}

@TECHREPORT{papka98online,
  AUTHOR = {Ron Papka and James Allan},
  TITLE = {On-line New Event Detection using Single-pass Clustering},
  INSTITUTION = {Department of Computer Science, University of Massachusetts},
  NUMBER = { UMASS Computer Science Technical Report 98 -- 21},
  YEAR = {1998},
  URL = {http://cobar.cs.umass.edu/pubfiles/ir-123.ps},
  ANNOTE = {Papka and Allan bring forward a single-pass clustering method modified from that of van Rijbergen, involving document queries and belief-thresholds. The paper also contains a brief TDT system comparison with the CMU and Dragon Systems.}
}

@INPROCEEDINGS{yang00improving,
  AUTHOR = {Yiming Yang and Thomas Ault and Thomas Pierce and Charles Lattimer},
  TITLE = {Improving Text Categorization Methods for Event Detection},
  BOOKTITLE = {Proc. ACM SIGIR},
  YEAR = {2000},
  PAGES = {65--72},
  URL = {http://www.cs.cmu.edu/~yiming/papers.yy/sigir00.ps.gz},
  ANNOTE = {A report on Event Detection with 'traditional' statistical learning. The group used TFIDF with Rocchio and kNN-variants.}
}

@ARTICLE{yang99learning,
  AUTHOR = {Yiming Yang and Jaime Carbonell and Ralf Brown and Thomas Pierce and Brian T. Archibald and  Xin Liu},
  TITLE = {Learning Approaches for Detecting and Tracking News Events},
  JOURNAL = {IEEE Intelligent Systems Special Issue on Applications of Intelligent Information Retrieval},
  VOLUME = {14},
  NUMBER = {4},
  YEAR = {1999},
  PAGES = {32 -- 43},
  URL = {http://www.cs.cmu.edu/~yiming/papers.yy/ieee99.tdt.pdf.gz},
  ANNOTE = {A good introduction to Event (Topic) Detection and Tracking}
}

@INPROCEEDINGS{yang98study,
  AUTHOR = {Yiming Yang and Thomas Pierce and Jaime Carbonell},
  TITLE = {A Study on Retrospective and On-Line Event Detection},
  BOOKTITLE = {Proc. ACM SIGIR},
  YEAR = {1998},
  PAGES = {28--36},
  ADDRESS = {Melbourne},
  URL = {http://www.cs.cmu.edu/~yiming/papers.yy/sigir98.ps.gz},
  ANNOTE = {The paper presents the CMU approach to event detection and corresponding results. They used GAC-clustering for retrospective and INCR clustering for on-line detection.}
}