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Learning approaches for detecting and tracking news events

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6 Author(s)
Yiming Yang ; Language Technol. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA ; Carbonell, J.G. ; Brown, R.D. ; Pierce, T.
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The authors extend existing supervised-learning and unsupervised-clustering algorithms to allow document classification based on the information content and temporal aspects of news events. They've adapted several IR and machine learning techniques for effective event detection and tracking. The article discusses our research using manually segmented documents

Published in:

Intelligent Systems and their Applications, IEEE  (Volume:14 ,  Issue: 4 )