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Using Fisher's Exact Test to Evaluate Association Measures for N-grams

2021-04-29 08:59:33
Yves Bestgen
arXiv_CL
 
Abstract

To determine whether some often-used lexical association measures assign high scores to n-grams that chance could have produced as frequently as observed, we used an extension of Fisher's exact test to sequences longer than two words to analyse a corpus of four million words. The results, based on the precision-recall curve and a new index called chance-corrected average precision, show that, as expected, simple-ll is extremely effective. They also show, however, that MI3 is more efficient than the other hypothesis tests-based measures and even reaches a performance level almost equal to simple-ll for 3-grams. It is additionally observed that some measures are more efficient for 3-grams than for 2-grams, while others stagnate.

Abstract (translated)

URL

https://arxiv.org/abs/2104.14209

PDF

https://arxiv.org/pdf/2104.14209.pdf

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