HAL : hal-00636111, version 1

DOI : 10.1016/j.ipm.2006.03.017

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Information Processing and Management 42, 6 (2006) 1532-1552

Textmining without document context.

Eric Sanjuan (  Auteur correspondant ) 1, Fidelia Ibekwe-Sanjuan (  Auteur correspondant ) 2

(15/12/2006)

We consider a challenging clustering task: the clustering of multi-word terms without document co-occurrence information in order to form coherent groups of topics. For this task, we developed a methodology taking as input multi-word terms and lexico-syntactic relations between them. Our clustering algorithm, named CPCL is implemented in the TermWatch system. We compared CPCL to other existing clustering algorithms, namely hierarchical and partitioning (k-means, k-medoids). This out-of-context clustering task led us to adapt multi-word term representation for statistical methods and also to refine an existing cluster evaluation metric, the editing distance in order to evaluate the methods. Evaluation was carried out on a list of multi-word terms from the genomic field which comes with a hand built taxonomy. Results showed that while k-means and k-medoids obtained good scores on the editing distance, they were very sensitive to term length. CPCL on the other hand obtained a better cluster homogeneity score and was less sensitive to term length. Also, CPCL showed good adaptability for handling very large and sparse matrices.

1 :	Laboratoire Informatique d'Avignon (LIA)
	Université d'Avignon – Centre d'Enseignement et de Recherche en Informatique - CERI
2 :	Equipe de recherche de Lyon en sciences de l'information et de la communication (ELICO)
	Université Lumière - Lyon II : EA4147 – Université Claude Bernard - Lyon I – Université Jean Moulin - Lyon III – Institut d'Études Politiques [IEP] - Lyon – École Nationale Supérieure des Sciences de l'Information et des Bibliothèques - Lyon

Domaine

:

Sciences de l'Homme et Société/Sciences de l'information et de la communication

Mots Clés : Multi-word term clustering – Lexico-syntactic relations – Text mining – Informetrics – Cluster evaluation

hal-00636111, version 1

http://hal.archives-ouvertes.fr/hal-00636111

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Contributeur : Fidelia Ibekwe-Sanjuan <>

Soumis le : Mercredi 2 Novembre 2011, 19:36:22

Dernière modification le : Jeudi 3 Novembre 2011, 17:02:07