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Communication Dans Un Congrès Année : 2003

Using belief networks and Fisher kernels for structured document classification

Résumé

We consider the classification of structured (e.g. XML) textual documents. We first propose a generative model based on Belief Networks which allows us to simultaneously take into account structure and content information. We then show how this model can be extended into a more efficient classifier using the Fisher kernel method. In both cases model parameters are learned from a labelled training set of representative documents. We present experiments on two collections of structured documents: WebKB which has become a reference corpus for HTML page classification and the new INEX corpus which has been developed for the evaluation of XML information retrieval systems.

Dates et versions

hal-01357596 , version 1 (30-08-2016)

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Ludovic Denoyer, Patrick Gallinari. Using belief networks and Fisher kernels for structured document classification. PKDD 2003 - 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Sep 2003, Cavtat-Dubrovnik, Croatia. pp.120-131, ⟨10.1007/978-3-540-39804-2_13⟩. ⟨hal-01357596⟩
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