Unsupervised Deep Learning for Vertical Conversational Chatbots

One approach to building conversational (dialog) chatbots is to use an unsupervised sequence-to-sequence recurrent neural network (seq2seq RNN) deep learning framework. About a year ago, researchers (Vinyals-Le) at Google published an ICML paper "A Neural Conversational Model" that describes one such framework; a review can be found here. The Vinyals-Le paper (and associated framework) is instructive in understanding some of the parameters of such seq2seq chatbot models. We assume that Vinyals-Le used Tensorflow, though this is not explicitly stated in the paper. Note that seq2seq may not be the best way to build a truly conversational chatbot; the Vinyals-Le chatbot is more of a Q/A system that originated in machine translation.