Abstract
This paper presents a conversation strategy for interactive recommendations using a chatbot. Chatbots are attracting attention to provide a flexible user interface using natural language for various domains. For a given task, what kind of questions to ask and/or what information should be provided and how to process user responses play a crucial role in developing an effective chatbot. In this paper, we focus on a task of recommending an item that suits a user’s preference and propose a conversation strategy where a chatbot combines questions about user’s preference and recommendations soliciting user’s feedback to them. The balance between questions and recommendations is controlled by changing the parameter values. We target a chatbot that uses a graphical user interface (GUI) and apply approaches proposed in the field of recommendation systems. Preliminary experiment results with a prototype indicate the potential of our proposed approach.
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Acknowledgment
This work was partially supported by JSPS KAKENHI Grant Number 15K00324.
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Ikemoto, Y., Asawavetvutt, V., Kuwabara, K., Huang, HH. (2018). Conversation Strategy of a Chatbot for Interactive Recommendations. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_11
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