Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots
Table 4: The effect of instance number
['[EMPTY]', 'LSTM2', 'LSTM5', 'LSTM10', 'LSTM20']
How the number of response candidates affects learning: we vary the number of {yi,j}nj=1 in D in {2,5,10,20} and study how the hyper-parameter influences learning. We study with LSTM on the STC data and SMN on the Douban data. We can see that as the number of candidates increases, the performance of the the learned models becomes better. Even with 2 candidates (one from human and the other from retrieval), our approach can still improve the peformance of matching models.