Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A symbolic approach to automatic multiword term structuring
Computer Speech and Language
Exploiting noun phrases and semantic relationships for text document clustering
Information Sciences: an International Journal
Progress in information retrieval
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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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.