Word association norms, mutual information, and lexicography
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Inducing a semantically annotated lexicon via EM-based clustering
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Annealing techniques for unsupervised statistical language learning
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Deep lexical acquisition of verb-particle constructions
Computer Speech and Language
Detecting noun compounds and light verb constructions: a contrastive study
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
Automatic retrieval of parallel collocations
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
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
Towards advanced collocation error correction in Spanish learner corpora
Language Resources and Evaluation
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In this paper we start to explore two-part collocation extraction association measures that do not estimate expected probabilities on the basis of the independence assumption. We propose two new measures based upon the well-known measures of mutual information and pointwise mutual information. Expected probabilities are derived from automatically trained Aggregate Markov Models. On three collocation gold standards, we find the new association measures vary in their effectiveness.