Graphic Representation and Visualisation as Modelling Support for the Knowledge Acquisition Process
Abstract: The thesis describes steps taken towards using graphic representation and visual modelling support for the knowledge acquisition process in knowledge-based systems – a process commonly regarded as difficult. The performance of the systems depends on the quality of the embedded knowledge, which makes the knowledge acquisition phase particularly significant. During the acquisition phase, a main obstacle to proper extraction of information is the absence of effective modelling techniques.The contributions of the thesis are: introducing a methodology for user-centred knowledge modelling, enhancing transparency to support the modelling of content and of the reasoning strategy, incorporating conceptualisation to simplify the grasp of the contents and to support assimilation of the domain knowledge, and supplying a visual compositional logic programming language for adding and modifying functionality.The user-centred knowledge acquisition model, proposed in this thesis, applies a combination of different approaches to knowledge modelling. The aim is to bridge the gap between the users (i.e., knowledge engineers, domain experts and end users) and the system in transferring knowledge, by supporting the users through graphics and visualisation. Visualisation supports the users by providing several different views of the contents of the system.The Unified Modelling Language (UML) is employed as a modelling language. A benefit of utilising UML is that the knowledge base can be modified, and the reasoning strategy and the functionality can be changed directly in the model. To make the knowledge base more comprehensible and expressive, we incorporated visual conceptualisation into UML’s diagrams to describe the contents. Visual conceptualisation of the knowledge can also facilitate assimilation in a hypermedia system through visual libraries.Visualisation of functionality is applied to a programming paradigm, namely relational programming, often employed in artificial intelligence systems. This approach employs Venn-Euler diagrams as a graphic interface to a compositional operator based relational programming language. The concrete result of the research is the development of a graphic representation and visual modelling approach to support the knowledge acquisition process. This approach has been evaluated for two different knowledge bases, one built for hydropower development and river regulation and the other for diagnosing childhood diseases.
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