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.

Abstract

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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