A parallel hierarchical agglomerative clustering technique for billingual corpora based on reduced terms with automatic weight optimization

Rayner Alfred, (2009) A parallel hierarchical agglomerative clustering technique for billingual corpora based on reduced terms with automatic weight optimization. In: 5th International Conference on Advanced Data Mining and Applications (ADMA), 17-19 August 2009, Beijing, China.

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Abstract

Multilingual corpora are becoming an essential resource for work in multilingual natural language processing. The aim of this paper is to investigate the effects of applying a clustering technique to parallel multilingual texts. It is interesting to look at the differences of the cluster mappings and the tree structures of the clusters. The effect of reducing the set of terms considered in clustering parallel corpora is also studied. After that, a genetic-based algorithm is applied to optimize the weights of terms considered in clustering the texts to classify unseen examples of documents. Specifically, the aim of this work is to introduce the tools necessary for this task and display a set of experimental results and issues which have become apparent. © 2009 Springer.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Billingual corpora, Hierarchical agglomerative clustering, Natural language processing, Parallel clustering
Subjects: ?? P98-98.5 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 25 Mar 2011 08:29
Last Modified: 30 Dec 2014 06:35
URI: http://eprints.ums.edu.my/id/eprint/2580

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