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Tech Report kmi-04-16 Abstract


An Ontology-Driven Similarity Algorithm
Techreport ID: kmi-04-16
Date: 2004
Author(s): Maria Vargas-Vera, Enrico Motta
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This paper presents our similarity algorithm between relations in a user query written in FOL (first order logic) and ontological relations. Our similarity algorithm takes two graphs and produces a mapping between elements of the two graphs (i.e. graphs associated to the query, a subsection of ontology relevant to the query). The algorithm assesses structural similarity and concept similarity. An evaluation of our algorithm using the KMi Planet ontology is presented. We also carried out an experiment to test the human judgment about similarity using context and without context. Our similarity algorithm has been mainly used in AQUA, our question answering system, in the query reformulation process.
 
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Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.