Artificial Conversations for Chatter Bots Using Knowledge Representation, Learning, and Pragmatics

Chatter bots are software programs that engage in artificial conversations through a text-based input medium. Many businesses have automated their online customer service support by deploying chatter bots. These customer service chatter bots interact with customers, answer their queries, and address service related issues. Traditional chatter bots perform best in artificial conversations consisting of pairs of utterance exchanges such as question-answer sessions, where the context may or may not switch with every exchange pair. They perform poorly in longer conversations, where the context is maintained over several pairs of utterance exchanges. Existing approaches to artificial conversation generation focus on linguistic and grammatical modeling using natural language processing and computational linguistics techniques to generate individual sentence-level utterances. This research explores techniques to go beyond individual sentence-level interactions to model the higher level conversation process. A conversation is a process

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