
arXiv: cs/0001012
We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.
9 pages, 3 figures
FOS: Computer and information sciences, Computer Science - Computation and Language, I.2.7, Computation and Language (cs.CL)
FOS: Computer and information sciences, Computer Science - Computation and Language, I.2.7, Computation and Language (cs.CL)
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