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Communication Dans Un Congrès Année : 2006

Phrase clustering without document context.

Résumé

We applied different clustering algorithms to the task of clus- tering multi-word terms in order to reflect a humanly built ontology. Clustering was done without the usual document co-occurrence infor- mation. Our clustering algorithm, CPCL (Classification by Preferential Clustered Link) is based on general lexico-syntactic relations which do not require prior domain knowledge or the existence of a training set. Results show that CPCL performs well in terms of cluster homogeneity and shows good adaptability for handling large and sparse matrices.
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Dates et versions

hal-00636150 , version 1 (26-10-2011)

Identifiants

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Eric Sanjuan, Fidelia Ibekwe-Sanjuan. Phrase clustering without document context.. 28th European Conference on Information Retrieval (ECIR-06)., Apr 2006, London, United Kingdom. pp.496-500, ⟨10.1007/11735106⟩. ⟨hal-00636150⟩
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