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Document Logical Structure Analysis Based on Perceptive Cycles

Identifieur interne : 001083 ( Main/Exploration ); précédent : 001082; suivant : 001084

Document Logical Structure Analysis Based on Perceptive Cycles

Auteurs : Yves Rangoni [France] ; Abdel Belaïd [France]

Source :

RBID : ISTEX:941221242190433760FC0F9CDB3B864820FE5AF5

Abstract

Abstract: This paper describes a Neural Network (NN) approach for logical document structure extraction. In this NN architecture, called Transparent Neural Network (TNN), the document structure is stretched along the layers, allowing an interpretation decomposition from physical (NN input) to logical (NN output) level. The intermediate layers represent successive interpretation steps. Each neuron is apparent and associated to a logical element. The recognition proceeds by repetitive perceptive cycles propagating the information through the layers. In case of low recognition rate, an enhancement is achieved by error backpropagation leading to correct or pick up a more adapted input feature subset. Several feature subsets are created using a modified filter method. The first experiments performed on scientific documents are encouraging.

Url:
DOI: 10.1007/11669487_11


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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