PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Relaxation Labeling for Selecting and Exploiting Efficiently Non-Local Dependencies in Sequence Labeling
Guillaume Wisniewski and Patrick Gallinari
In: PKDD'07, 17-21 Sep 2007, Warsaw, Poland.


We consider the problem of sequence labeling and propose a two steps method which combines the scores of local classifiers with a relaxation labeling technique. This framework can account for sparse dynamically changing dependencies, which allows us to efficiently discover relevant non-local dependencies and exploit them. This is in contrast to existing models which incorporate only local relationships between neighboring nodes. Experimental results show that the proposed method gives promising results.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3664
Deposited By:Guillaume Wisniewski
Deposited On:14 February 2008