Siamese Neural Networks with Random Forest for detecting duplicate question pairs
Table 1: Dataset augmentation details
['[BOLD] Data', '[BOLD] Before', '[BOLD] After']
The first type of augmentation is necessary for improving the response of the Siamese arms to flipped input. Accordingly, the dataset is augmented by flipping the question pairs. Additional positive samples are generated by pairing each unique question with itself. Finally, negative samples are generated to balance the augmented dataset by randomly selecting 2 questions that do not have common known duplicates. This augmented data was not used for training the secondary classifier.