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1 Introduction The book presents a model of interactive explanation generation and its implementation as the tutorial dialogue system EDGE (Explanatory Discourse GEnerator). EDGE produces explanations on electronic circuits and, by entering a dialogue with the user, is able to adjust its explanations according to the user's background knowledge and her(More)
Con#ict situations do not only arise from misunderstandings, erroneous perceptions, partial knowledge, false beliefs, etc., but also from di!erences in &&opinions'' and in the di!erent agents' value systems. It is not always possible, and maybe not even desirable, to &&solve'' this kind of con#ict, as the sources are subjective. The communicating agents(More)
This paper presents an approach for providing patients with personalised explanations of their medical record. Simple text planning techniques are used to construct relevant explanations based on information in the record and information in a general medical knowledge base. We discuss the results of the evaluation of our system with diabetes patients at(More)
OBJECTIVE To compare the use and effect of a computer based information system for cancer patients that is personalised using each patient's medical record with a system providing only general information and with information provided in booklets. DESIGN Randomised trial with three groups. Data collected at start of radiotherapy, one week later (when(More)
In this paper we describe the evaluation of a personalised information system for patients with cancer. Our system dynamically generates hypertext pages that explain treatments, diseases, measurements etc related to the patient's condition, using information in the patient's medical record as the basis for the tailoring. We describe results of a controlled(More)
In this paper I consider how user modelling can be used to improve the provision of complex explanations, and discuss in detail the user modelling component of the EDGE explanation system. This allows a user model to be both updated and used in an explanatory dialogue with the user. The model is updated based on the interactions with the user, relationships(More)
An important part of building a natural-language generation (NLG) system is knowledge acquisition, that is deciding on the specific schemas, plans, grammar rules, and so forth that should be used in the NLG system. We discuss some experiments we have performed with KA for content-selection rules, in the context of building an NLG system which generates(More)
Good communication is vital in health care, both among health care professionals, and between health care professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying, and even more convincing than the structured data, even when presented in(More)