Modeling Psychotherapy Dialogues with Kernelized Hashcode Representations:A Nonparametric Information-Theoretic Approach
(a) Depression Therapy Dataset
['[BOLD] Model', 'Average', 'Greedy', 'Extrema']
Overall, the proposed hashing approaches are quite competitive with the neural net methods in terms of those metrics as well: on all three datasets, our LSH methods always outperform their competitors in terms of the average similarity metric (which is the most intuitive among the three metrics in terms of reflecting the topic similarity between the true and system-generated responses); moreover, our methods also achieve best performance w.r.t. the greedy metric on Twitter dataset, and w.r.t. extrema metric on the Depression dataset.