Word association norms, mutual information, and lexicography
Computational Linguistics
Multiword Expressions: A Pain in the Neck for NLP
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Retrieving collocations from text: Xtract
Computational Linguistics - Special issue on using large corpora: I
Multiword unit hybrid extraction
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Using small random samples for the manual evaluation of statistical association measures
Computer Speech and Language
Task-based evaluation of multiword expressions: a pilot study in statistical machine translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Multiword expressions in the wild?: the mwetoolkit comes in handy
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations
Pre- and postprocessing for statistical machine translation into Germanic languages
HLT-SS '11 Proceedings of the ACL 2011 Student Session
Detecting multi-word expressions improves word sense disambiguation
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
Identifying and analyzing Brazilian Portuguese complex predicates
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
Identification and treatment of multiword expressions applied to information retrieval
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
A broad evaluation of techniques for automatic acquisition of multiword expressions
ACL '12 Proceedings of ACL 2012 Student Research Workshop
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This paper presents an open and flexible methodological framework for the automatic acquisition of multiword expressions (MWEs) from monolingual textual corpora. This research is motivated by the importance of MWEs for NLP applications. After briefly presenting the modules of the framework, the paper reports extrinsic evaluation results considering two applications: computer-aided lexicography and statistical machine translation. Both applications can benefit from automatic MWE acquisition and the expressions acquired automatically from corpora can both speed up and improve their quality. The promising results of previous and ongoing experiments encourage further investigation about the optimal way to integrate MWE treatment into these and many other applications.