Phrase Clustering Without Document Context

Abstract. We applied different clustering algorithms to the task of clustering multi-word terms in order to reflect a humanly built ontology. Clustering was done without the usual document co-occurrence information. 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.

• Type: Conference
• Year: 2006
• Where: ECIR
• Authors: Eric SanJuan, Fidelia Ibekwe-Sanjuan
• Keywords: Clustering Algorithm, ECIR 2006, Humanly Built Ontology, Information Technology, Usual Document Co-occurrence