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Question Understanding based on Sentence Embedding on Dialog Systems for Banking Service


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Abstract


This paper introduce a question understanding system to respond appropriate answers in a dialog system for banking services. The question understanding system provides an automated response service in a specific domain (e.g. banking). This can increase response rate of a customer counseling service, and improve business efficiency and expertise. The question understanding system classify domains, specific categories, and speech acts of questions. Finally, the system analyze meanings and intents of the questions, and searching correct answers even various input sentences. In this paper, we describe methods of keyword tokenizing, pattern recognition, sentence embedding, analyzing dialogue intention, and searching similar FAQs. Through these methods, we have developed the question understanding unit in a real interactive system for financial services for real insurance companies and banks, and analyze the usefulness of the system through practical system implementation examples

KeyWords
natural language understanding sentence embedding document classification intent recognition



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