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KMi Seminars
Using the Dempster-Shafer theory of evidence to resolve ABox inconsistencies
This event took place on Wednesday 07 November 2007 at 11:30

 
Andriy Nikolov Computing Research Centre, The Open University, UK

Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms may serve as evidence helping to repair produced inconsistencies. Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors’
confidence values. The talk presents an algorithm for translating the subontologies containing conflicts into belief propagation networks and repairing conflicts based on Dempster-Shafer plausibility.

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

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.