Tuning a conversation strategy for interactive recommendations in a chatbot setting. Issue 2 (3rd April 2019)

• Record Type: Journal Article
• Authors: Ikemoto, Yuichiro; Asawavetvutt, Varit; Kuwabara, Kazuhiro; Huang, Hung-Hsuan
• Is Part Of: Journal of information and telecommunication. Volume 3:Issue 2(2019)
• Page Start: 180
• Page End: 195
• Publication Date: 2019-04-03
• Subjects: Conversation strategy -- chatbot -- interactive recommendation -- simulation; Telecommunication -- Periodicals; Information technology -- Periodicals; 621.382
• DOI: 10.1080/24751839.2018.1544818
• Languages: English
• ISSNs: 2475-1839

Abstract

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.