Fouille de textes par combinaison de règles d'association et d'indices statistiques
Identifieur interne : 008434 ( Main/Merge ); précédent : 008433; suivant : 008435Fouille de textes par combinaison de règles d'association et d'indices statistiques
Auteurs : Hacène Cherfi [France] ; Yannick Toussaint [France]Source :
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Abstract
Nous proposons la description d'une méthodologie d'accès et de lecture des règles d'association extraites à partir de textes. Le corpus ayant servi à notre expérimentation est constitué de résumés d'articles scientifiques dans le domaine de la biologie moléculaire. Ce processus génère un trop grand nombre de règles et nous amène à chercher à les trier de la plus informative à la moins informative.Le classement est établi suivant des indices statistiques. Une discussion sur nos résultats identifie quelques points ayant un impact sur l'interprétabilité des règles d'association. || This paper aims at defining a methodology of access and reading of association rules extracted from texts. The corpus used is a set of scientific abstracts in the field of molecular biology. The mining process often generates a huge number of rules. This
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Hal:inria-00107581Le document en format XML
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type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>association rules</term><term>fouille de textes</term><term>indices statistiques</term><term>interprétation</term><term>règles d'association</term><term>statistical indices</term><term>terminologie</term><term>terminology</term><term>text mining</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="fr">Nous proposons la description d'une méthodologie d'accès et de lecture des règles d'association extraites à partir de textes. Le corpus ayant servi à notre expérimentation est constitué de résumés d'articles scientifiques dans le domaine de la biologie moléculaire. Ce processus génère un trop grand nombre de règles et nous amène à chercher à les trier de la plus informative à la moins informative.Le classement est établi suivant des indices statistiques. Une discussion sur nos résultats identifie quelques points ayant un impact sur l'interprétabilité des règles d'association. || This paper aims at defining a methodology of access and reading of association rules extracted from texts. The corpus used is a set of scientific abstracts in the field of molecular biology. The mining process often generates a huge number of rules. This</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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