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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
 

Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.