Abstract
This paper describes the user modeling component of EPIAIM, a consultation system for data analysis in epidemiology. The component is aimed at representing knowledge of concepts in the domain, so that their explanations can be adapted to user needs. The first part of the paper describes two studies aimed at analysing user requirements. The first one is a questionnaire study which examines the respondents' familiarity with concepts. The second one is an analysis of concept descriptions in textbooks and from expert epidemiologists, which examines how discourse strategies are tailored to the level of experience of the expected audience. The second part of the paper describes how the results of these studies have been used to design the user modeling component of EPIAIM. This module works in a two-step approach. In the first step, a few trigger questions allow the activation of a stereotype that includes a “body” and an “inference component”. The body is the representation of the body of knowledge that a class of users is expected to know, along with the probability that the knowledge is known. In the inference component, the learning process of concepts is represented as a belief network. Hence, in the second step the belief network is used to refine the initial default information in the stereotype's body. This is done by asking a few questions on those concepts where it is uncertain whether or not they are known to the user, and propagating this new evidence to revise the whole situation. The system has been implemented on a workstation under UNIX. An example of functioning is presented, and advantages and limitations of the approach are discussed.
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Fiorella de Rosis is associate professor of Computer Science at the University of Bari. For several years after her thesis in Theoretical Computer Science at the University of Rome, she did research in Medical Informatics. From 1986, her primary interests lie in the area of uncertainty, task and user modeling, adaptivity of interaction. She was responsible for the Bari University group, in the European Community Project EPIAIM.
Sebastiane Pizzutilo is a senior researcher in Computer Science at the University of Bari, where he received his degree in Computer Science in 1975. He teaches computer architectures within the Bari university curriculum in Computer Science. His current research includes the fields of object-oriented data and knowledge bases and of intelligent interfaces.
Alesandra Russo is a PhD candidate in Computer Science at the Imperial College of Science and Technology in London. She received her degree in Computer Science from the University of Bari in 1990, after having prepared a thesis at the University of Paris 5, in the framework of an ERASMUS Project.
Diane Berry is a lecturer in psychology at the University of Reading. Prior to this she was a research fellow and lecturer in psychology at Balliol College, Oxford. She has a first class degree in psychology and a doctorate in experimental psychology. For the last 10 years, she has been researching in the area of human computer interaction.
F. Javier Nicolau Molina is a researcher at INSERM in Paris. He received his degree in Computer Science at the University of Barcelona in 1986 and a Master(DEA) in Medical Informatics from the University of Paris 5 in 1989. In the EPIAIM Project he was responsible for building the user modeling module and the generator of adaptive messages in an objectoriented language.
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De Rosis, F., Pizzutilo, S., Russo, A. et al. Modeling the user knowledge by belief networks. User Model User-Adap Inter 2, 367–388 (1992). https://doi.org/10.1007/BF01101110
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DOI: https://doi.org/10.1007/BF01101110