PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Conditional Random Field for tracking user behaviour based on his eye's movements
T.M.T. Do and thierry artieres
In: NIPS 2005 Workshop on Machine Learning for Implicit Feedback and User Modeling, 10 December 2005, Whistler, Canada.


Conditional Random Fields offer some advantages over traditional models for sequence labeling. These conditional models have mainly been introduced up to now in the information retrieval context for information extraction or POS-tagging tasks. This paper investigates the use of these models for signal processing and segmentation. In this context, the input we consider is a signal that is represented as a sequence of real-valued feature vectors and the training is performed using only partially labeled data. We propose a few models for dealing with such signals and provide experimental results on the data from the eye movement challenge.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Information Retrieval & Textual Information Access
ID Code:1652
Deposited By:Thierry Artieres
Deposited On:28 November 2005