PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Stacked dependency networks for layout document structuring
Boris Chidlovskii and Loïc Lecerf
In: SIGIR Information Retrieval and Graphical Model Workshop, July 25 ,2007, Amsterdam, The Netherlands.

Abstract

We address the problems of the structuring and annotation of layout-oriented documents. We model the annotation problems as the collective classification on graph-like strucutres with typed instances and links that capture the domain-specific knowledge. We use the relational dependency networks (RDNs) for the collective inference on the multi-typed graphs. We describe them a variant of RDNs where a stacked approximation replaces the Gibbs sampling in order to accelerate the inference. We report results of evaluation tests for both the Gibbs sampling and stacking inference on two document structuring examples

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:3042
Deposited By:Boris Chidlovskii
Deposited On:16 September 2007