Table 4.

Bootstrap resamplings and average precision

Same-Stem Pairs		Different-Stem Pairs
Data set	Average Precision (95% CI)	Data set	Average Precision (95% CI)
word2vec-GloVe*	0.0370 (0.0190–0.0564)	fastText-GloVe	0.0699 (−0.0026 to 0.1416)
word2vec-FastText*	0.0619 (0.0321–0.0942)	fastText-word2vec	0.0453 (−0.0242 to 0.1157)
GloVe-FastText	0.0249 (−0.0087–0.0594)	GloVe-word2vec	0.0246 (−0.0171 to 0.0649)

Note: There were 10 000 bootstrap resamplings for each data set. For each sample, we computed the average precision for each of the 3 embedding methods. This allowed us to compare the performance of the methods as the difference in average precision on each sample and compute the mean and 95% confidence interval for each comparison. We found that word2vec is better than GloVe or fastText on the same-stem data. *Significant difference at the 5% level.

CI: confidence interval.