Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots

Understand

We study response selection for multi-turn conversation in retrieval-based chatbots.

• Existing work either concatenates utterances in context or matches a response with a highly abstract context vector finally, which may lose relationships among utterances or important contextual information.
• We propose a sequential matching network (SMN) to address both problems.
• SMN first matches a response with each utterance in the context on multiple levels of granularity, and distills important matching information from each pair as a vector with convolution and pooling operations.