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We examine the implementation of clarification dialogues, a mechanism for ensuring that question answering systems take into account user goals by allowing them to ask series of related questions either by refining or expanding on previous questions with follow-up questions, in the context of open domain Question Answering systems. We develop an algorithm for clarification dialogue recognition through the analysis of collected data on clarification dialogues and examine the importance of clarification dialogue recognition for question answering. The algorithm is evaluated and shown to successfully recognize the start and continuation of clarification dialogues in 94% of cases. We then show the usefulness of the algorithm by demonstrating how the recognition of clarification dialogues can simplify the task of answer retrieval.

We examine clarification dialogue, a mechanism for refining user questions with follow-up questions, in the context of open domain Question Answering systems. We develop an algorithm for clarification dialogue recognition through the analysis of collected data on clarification dialogues and examine the importance of clarification dialogue recognition for question answering. The algorithm is evaluated and shown to successfully recognize the occurrence of clarification dialogue in the majority of cases and to simplify the task of answer retrieval.

Argumentation is an emerging topic in the field of human computer dialogue. In this paper we describe a novel approach to dialogue management that has been developed to achieve persuasion using a textual argumentation dialogue system. The paper introduces a layered management architecture that mixes task-oriented dialogue techniques with chatbot techniques to achieve better persuasiveness in the dialogue.

We built an automated dialogue system whose style of interaction can be varied along the three dimensions of Humour, Relationship Maintenance and Personality Matching. We then ran a longitudinal experiment which investigated manipulations of these three dimensions. We explored the interaction of these separate dimensions on user perception of the system using a controlled study design. We showed a strong positive effect for the use of Humour and Relationship Maintenance, while the use of Personality Matching raised a number of questions which need further investigation.