Automatic Indexing from a Thesaurus Using Bayesian Networks: Application to the Classification of Parliamentary Initiatives
Identifieur interne : 000491 ( Istex/Checkpoint ); précédent : 000490; suivant : 000492Automatic Indexing from a Thesaurus Using Bayesian Networks: Application to the Classification of Parliamentary Initiatives
Auteurs : Luis M. De Campos [Espagne] ; Juan M. Fernández-Luna [Espagne] ; Juan F. Huete [Espagne] ; Alfonso E. Romero [Espagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: We propose a method which, given a document to be classified, automatically generates an ordered set of appropriate descriptors extracted from a thesaurus. The method creates a Bayesian network to model the thesaurus and uses probabilistic inference to select the set of descriptors having high posterior probability of being relevant given the available evidence (the document to be classified). We apply the method to the classification of parliamentary initiatives in the regional Parliament of Andalucía at Spain from the Eurovoc thesaurus.
Url:
DOI: 10.1007/978-3-540-75256-1_75
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: We propose a method which, given a document to be classified, automatically generates an ordered set of appropriate descriptors extracted from a thesaurus. The method creates a Bayesian network to model the thesaurus and uses probabilistic inference to select the set of descriptors having high posterior probability of being relevant given the available evidence (the document to be classified). We apply the method to the classification of parliamentary initiatives in the regional Parliament of Andalucía at Spain from the Eurovoc thesaurus.</div>
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