Grounding the detection of the user’s likes and dislikes on the topic structure of human-agent interactions

This paper introduces a knowledge-based system which grounds the detection of the user’s likes and dislikes on the topic structure of the conversation. The targeted study is set in a human-agent interaction with the aim to help the creation of dialogue strategies of an agent based on the user’s interests. In this paper, we first describe the system based on linguistic resources such as lexicons, dependency grammars and dialogue information provided by the dialogue system. Second, we explain how the system merges its outputs at the end of each topic sequence. Finally, we present an evaluation of both the linguistic rules and the merging process. The system enables a better identification of the target of the user’s likes and dislikes and provides a synthetic representation of the user’s interests.