Abstract
This paper describes a novel intellectual structure for the subject space of material designed for selective autodidactic learning in a large knowledge base. This structure is based on a systematic theory-driven connection of categorical and factual knowledge. It is further based on the idea, that relevant subjects in such a system should be propositions, represented as categorical relationships. Informal inferences between concept hierarchies and categorical relationships are presented. The structure is implemented in a system for training of art conservators in diagnostic knowledge. Multiple systematic ways are implemented to give the user access and overview over large amounts of such subject propositions, that try to overcome the typical mismatch between a user-formulated request and the terms understood by the system, and the general disorientation of users in larger electronic media. The system is right now being presented to users with a first small population of cases.
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Doerr, M. (2005). Modelling Learning Subjects as Relationships. In: Grieser, G., Tanaka, Y. (eds) Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets. Lecture Notes in Computer Science(), vol 3359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32279-5_14
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DOI: https://doi.org/10.1007/978-3-540-32279-5_14
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