Abstract
The process of determining the principal topic of a Knowledge base (KB), and whether it conforms to a set of user-defined constraints, are important steps in the reuse of Knowledge Bases. We refer to these steps as the process of characterization of a Knowledge Base. Identify-Knowledge-Base (IKB) is a tool, which suggests the principal topic(s) addressed by the Knowledge Base. It matches concepts extracted from a particular knowledge base against some reference taxonomy, where the taxonomy can be pre-stored or extracted from ontologies which are either stored on the local machine or are assessable through the WWW. The ‘most specific’ super-concept subsuming these concepts is said to be the principal topic of the knowledge base. Additionally, a series of filters, which check if a KB has particular characteristics have been implemented. This paper describes both the Identify-Knowledge Base system and these filters. Some empirical studies of IKB and the filters with a range of problems are also reported.
This work is part of the Advanced Knowledge Technology (AKT) project, which is funded by EPSRC, [1]. The IKB system incorporates the ExtrAKT system [3, 4, 5] and interfaces with the Edinburgh Knowledge Broker [6, 7] which were built by the other members of the AKT consortium
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Sleeman, D., Zhang, Y., Vasconcelos, W. (2004). Characterisation of Knowledge Bases. In: Bramer, M., Ellis, R., Macintosh, A. (eds) Applications and Innovations in Intelligent Systems XI. SGAI 2003. Springer, London. https://doi.org/10.1007/978-1-4471-0643-2_17
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DOI: https://doi.org/10.1007/978-1-4471-0643-2_17
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