Exploring the Effectiveness of Convolutional Neural Networksfor Answer Selection in End-to-End Question Answering
Table 3. Results comparing our baselines, our CNN model, and the state of the art on the TrecQA dataset.
['[BOLD] Method', '[BOLD] MAP', '[BOLD] MRR']
We adopted the same experimental procedures and settings as Rao et al. Against this CNN for answer selection, we compared two very simple baselines: Let’s take a step back and consider the broader context of these results. (note this is a different paper than the one cited above). We make two interesting observations: Due to the sparsity of judgments, the absolute scores are low, and furthermore it is not clear if our CNN is actually more effective than idf-weighted word overlap!