Abstract
Generic conversational agents often use hard-coded stimulus-response data to generate responses, for which little to no effort is attributed to effectively understand and comprehend the input. The limitation of these types of systems is obvious: the general and linguistic knowledge of the system is limited to what the developer of the system explicitly defined. Therefore, a system which analyses user input at a deeper level of abstraction which backs its knowledge with common sense information will essentially result in a system that is capable of providing more adequate responses which in turn result in a better overall user experience.
From this premise, a framework was proposed, and a working prototype was implemented upon this framework. The prototype makes use of various natural language processing tools, online and offline knowledge bases, and other information sources, to enable it to comprehend and construct relevant responses.
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Dingli, A., Scerri, D. (2013). Building a Hybrid: Chatterbot – Dialog System. In: Habernal, I., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2013. Lecture Notes in Computer Science(), vol 8082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40585-3_19
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DOI: https://doi.org/10.1007/978-3-642-40585-3_19
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