Autores
Sidorov Grigori
Gelbukh Alexander
Guzmán Arenas Adolfo
Título Use of a weighted topic hierarchy for document classification
Tipo Congreso
Sub-tipo JCR
Descripción Lecture Notes in Artificial Intelligence; Second International Workshop, TSD’99
Resumen A statistical method of document classification driven by a hierarchical topic dictionary is proposed. The method uses a dictionary with a simple structure and is insensible to inaccuracies in the dictionary. Two kinds of weights of dictionary entries, namely, relevance and discrimination weights are discussed. The first type of weights is associated with the links between words and topics and between the nodes in the tree, while the weights of the second type depend on user database. A common sense-complaint way of assignment of these weights to the topics is presented. A system for text classification Classifier based on the discussed method is described.
Observaciones Second International Workshop, TSD’99 Plzen, Czech Republic, 1999 Proceedings
Lugar Czech
País República Checa
No. de páginas 133-138
Vol. / Cap. 1692
Inicio 1999-09-13
Fin 1999-09-17
ISBN/ISSN 978-3-540-48239-0