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
Automatic identification of non-compositional phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Automatic identification of non-compositional multi-word expressions using latent semantic analysis
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Using information about multi-word expressions for the word-alignment task
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Detecting complex predicates in Hindi using POS projection across parallel corpora
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Mining complex predicates in Hindi using a parallel Hindi-English corpus
MWE '09 Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications
Learning Disambiguation of Hindi Morpheme "vaalaa' with a Sparse Corpus
ICMLA '09 Proceedings of the 2009 International Conference on Machine Learning and Applications
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Relative compositionality of multi-word expressions: a study of verb-noun (v-n) collocations
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
SSST-6 '12 Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation
Learning to detect english and hungarian light verb constructions
ACM Transactions on Speech and Language Processing (TSLP) - Special issue on multiword expressions: From theory to practice and use, part 1
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Multi-word expressions (MWEs) play an important role in all tasks that involve natural language processing. MWEs in Hindi are quite varied and many of these are of the types that are not encountered in English. In this paper, we examine different types of MWEs encountered in Hindi. Many of these have not received adequate attention of investigators. For example, 'vaalaa' constructs, doublets (word-pairs), replication, and a variety of verb group forms have not been explored as MWEs. We examine these MWEs from machine translation viewpoint. Many of these are frequently used in day-to-day conversations and informal communication but are not that frequently encountered in a formal textual corpus. Most of the conventional statistical methods for MWE identification use corpus with limited linguistic cues. These are found to be inadequate for detecting all types of MWEs that exist in real life. In this paper, we present a stepwise methodology for mining Hindi MWEs using linguistic knowledge. Interpretation and representation for some of these from machine translation perspective have also been explored.