A hierarchical consensus architecture for robust document clustering

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Resumen

A major problem encountered by text clustering practitioners is the difficulty of determining a priori which is the optimal text representation and clustering technique for a given clustering problem. As a step towards building robust document partitioning systems, we present a strategy based on a hierarchical consensus clustering architecture that operates on a wide diversity of document representations and partitions. The conducted experiments show that the proposed method is capable of yielding a consensus clustering that is comparable to the best individual clustering available even in the presence of a large number of poor individual labelings, outperforming classic non-hierarchical consensus approaches in terms of performance and computational cost.

Idioma originalInglés
Título de la publicación alojadaAdvances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings
EditorialSpringer Verlag
Páginas741-744
Número de páginas4
ISBN (versión impresa)3540714944, 9783540714941
DOI
EstadoPublicada - 2007
Evento29th European Conference on IR Research, ECIR 2007 - Rome, Italia
Duración: 2 abr 20075 abr 2007

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4425 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia29th European Conference on IR Research, ECIR 2007
País/TerritorioItalia
CiudadRome
Período2/04/075/04/07

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