Boosting algorithm with sequence-loss cost function for structured prediction

Authors:
Tomasz Kajdanowicz;Przemysław Kazienko;Jan Kraszewski
Affiliations:
Wrocław University of Technology, Wrocław, Poland;Wrocław University of Technology, Wrocław, Poland;University of Wroclaw, Wrocław, Poland
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Year:
2010

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Abstract

The problem of sequence prediction i.e annotating sequences appears in many problems across a variety of scientific disciplines, especially in computational biology, natural language processing, speech recognition, etc The paper investigates a boosting approach to structured prediction, AdaBoostSTRUCT, based on proposed sequence-loss balancing function, combining advantages of boosting scheme with the efficiency of dynamic programming method In the paper the method's formalism for modeling and predicting label sequences is introduced as well as examined, presenting its validity and competitiveness.