Emulating Human Conversations using Convolutional Neural Network-based IR
Table 3: Precision@1 together with 95% confidence intervals. The best-performing baseline and experimental systems are shown in bold.
['[BOLD] Technique', '[BOLD] P@1', '[BOLD] 95% CI']
To assess the precision of retrieval, we also used a more conservative measure. Responses that achieved a supermajority of votes (≥4) were assigned a score of 1, otherwise they were assigned 0. This we will term Precision@1, in other words, precision at rank 1. It is evident from the confidence intervals that using features from deep learning models (i.e., cDSSM) to capture deep structured similarity yields significant improvement over other methods.