@inproceedings{ad40859a45774d078320aa91ec501c01,
title = "Characterisation of knowledge bases",
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.",
author = "Derek Sleeman and Yanren Zhang and Vasconcelos, {Wamberto W M P D}",
year = "2004",
language = "English",
isbn = "9781852337797",
series = "BCS Conference Series",
publisher = "Springer-Verlag",
pages = "235--246",
editor = "Max Bramer and Richard Ellis and Ann Macintosh",
booktitle = "Applications and Innovations in Intelligent Systems XI",
}