Multiword Expressions: A Pain in the Neck for NLP
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
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Computational Linguistics - Special issue on using large corpora: I
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An empirical model of multiword expression decomposability
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
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HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
SVM based Manipuri POS tagging using SVM based identified reduplicated MWE (RMWE)
Proceedings of the CUBE International Information Technology Conference
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One of the key issues in both natural language understanding and generation is the appropriate processing of Multiword Expressions (MWEs). MWE can be defined as a semantic issue of a phrase where the meaning of the phrase may not be obtained from its constituents in a straightforward manner. This paper presents an approach of identifying bigram noun-noun MWEs from a medium-size Bengali corpus by clustering the semantically related nouns and incorporating a vector space model for similarity measurement. Additional inclusion of the English WordNet::Similarity module also improves the results considerably. The present approach also contributes to locate clusters of the synonymous noun words present in a document. Experimental results draw a satisfactory conclusion after analyzing the Precision, Recall and F-score values.