%0 Journal Article
%T Tuning a conversation strategy for interactive recommendations in a chatbot setting
%A Hung-Hsuan Huang
%A Kazuhiro Kuwabara
%A Varit Asawavetvutt
%A Yuichiro Ikemoto
%J Journal of Information and Telecommunication
%D 2019
%R https://doi.org/10.1080/24751839.2018.1544818
%X ABSTRACT This paper presents a conversation strategy for interactive recommendations using a chatbot. Chatbots have recently been attracting attention for their use as a flexible user interface. To develop an effective chatbot, it is important to determine what kind of questions to ask, what information should be provided, and how to process a user's responses for a given task. In this paper, we target a chatbot that uses a graphical user interface (GUI) and focus on the task of recommending an item that suits a user's preference. We propose a conversation strategy where a chatbot combines questions about a user's preferences and recommendations while soliciting user's feedback to them. The balance between the questions and recommendations is controlled by changing the parameter values. In addition, we propose a simulation model to evaluate the performance of interactive recommendation under different parameter values. The simulation results with a prototype dataset are presented and discussed
%U https://www.tandfonline.com/doi/full/10.1080/24751839.2018.1544818