Word association norms, mutual information, and lexicography
Computational Linguistics
Principled disambiguation: discriminating adjective senses with modified nouns
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Retrieving collocations from text: Xtract
Computational Linguistics - Special issue on using large corpora: I
A statistical information extraction system for Turkish
Natural Language Engineering
Retrieving collocations by co-occurrences and word order constraints
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Methods for the qualitative evaluation of lexical association measures
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Integrating morphology with multi-word expression processing in Turkish
MWE '04 Proceedings of the Workshop on Multiword Expressions: Integrating Processing
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Collocation is the combination of words in which words appear together more often than by chance. Since collocations are blocks of meaning, they play an important role in natural language processing applications (word sense disambiguation, part of speech tagging, machine translation, etc). In this study, a corpus of Turkish is subjected to the following statistical techniques: frequency of occurrence, mutual information and hypothesis tests. We have utilized both stemmed and surface form of corpus to explore the effect of stemming in collocation extraction. The techniques are evaluated by recall and precision measures. Chi-square hypothesis test and mutual information methods have produced better results compared to other methods on Turkish corpus. In addition, we have found that a stemmed corpus facilitates discrimination between successful and unsuccessful collocation extraction methods.