An Evaluation Framework for Semantic Metadata
This event took place on Wednesday 24 October 2007 at 11:30
Yuangui Lei KMi, The Open University
Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developed to date. In this context, we proposed i) an evaluation reference model, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, which provides a set of instruments to support the
detection of quality problems and the collection of quality metrics
for these problems. In this talk, I will present the reference model and evaluation framework.
(Due to upgrading of webcasting facility this event will not be available as a webcast or a replay)
This event took place on Wednesday 24 October 2007 at 11:30
Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developed to date. In this context, we proposed i) an evaluation reference model, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, which provides a set of instruments to support the
detection of quality problems and the collection of quality metrics
for these problems. In this talk, I will present the reference model and evaluation framework.
(Due to upgrading of webcasting facility this event will not be available as a webcast or a replay)
Future Internet
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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.
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