Enriching Chatter Bots With Semantic Conversation Control

Abstract

Businesses deploy chatter bots to engage in text based conversations with customers that are intended resolve their issues. However, these chatter bots are only effective in exchanges consisting of question answer pairs, where the context may switch with every pair. I am designing a semantic architecture that enables chatter bots to hold short conversations, where context is maintained throughout the exchange. I leverage specific ideas from conversation theory, speech acts theory, and knowledge representation. My architecture models a conversation as a stochastic process that flows through a set of states. The main contribution of this work is that it analyses and models the semantics of conversations as entities, instead of lower level grammatical and linguistics forms. I evaluate the performance of the architecture in accordance with Grice's cooperative maxims, which form the central idea in the theory of pragmatics.