KMi Seminars
Approximation for the Semantic Web
This event took place on Friday 05 May 2006 at 12:30

 
Dr. Holger Wache Vrije Universiteit Amsterdam

Scalable reasoning for the Semantic Web is a crucial issue. Without scalability the Semantic Web will not be able to reason about the high and growing amount of data with respect to time performance and tolerant reasoning. Approximate reasoning seems to be a promising approach to introduce scalability to the Semantic Web.

Different forms of approximated reasoning are possible. First the reasoning process itself can be approximated by replacing the inference engine by a sophisticated approximated one. Second the knowledge, i.e. the ontology, can be weakened or, third, translated into another representation formalism. Obviously during both transformations knowledge is lost.

This talk reports about the investigation and experiences made in KNOWLEDGEWEB, an EU-funded network of excellence. The logical foundation of some approaches is briefly explained but also their practical consequences for scalable reasoning will be investigated.

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KMi Seminars
 

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.