Use of a weighted topic hierarchy for document classification?

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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.

Idioma originalInglés
Título de la publicación alojadaText, Speech and Dialogue - 2nd International Workshop, TSD 1999, Proceedings
EditoresVáclav Matousek, Pavel Mautner, Jana Oceláková, Petr Sojka
EditorialSpringer Verlag
Páginas133-138
Número de páginas6
ISBN (versión impresa)3540664947, 9783540664949
DOI
EstadoPublicada - 1999
Evento2nd International Workshop on Text, Speech and Dialogue, TSD 1999 - Plzen, República Checa
Duración: 13 sep. 199917 sep. 1999

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen1692
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia2nd International Workshop on Text, Speech and Dialogue, TSD 1999
País/TerritorioRepública Checa
CiudadPlzen
Período13/09/9917/09/99

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