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.

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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
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