Tech Reports
Tech Report kmi-08-03 Abstract
Modelling social context to improve online multimedia search
Techreport ID: kmi-08-03
Date: 2008
Author(s): Adam Rae
As the cost of production, storage and dissemination has plummeted for images, audio and video, challenges have arisen regarding how to most e?ectively handle this wealth of information. Digital recording devices have become cheaper, more widely available and are able to recording in better quality than ever before. Media representation has given us lossy and lossless file formats suitable for many different situations, from satellite broadcast to mobile streaming, each with their unique requirements and capabilities. Digital file storage devices have grown more capacious, high performing and more reliable. The one area that has not caught up is how to search and retrieval multimedia efficiently and e?ectively in these new, vast data sets and this is the focus for my work. More specifically, I wish to investigate the relationship between social context data and its e?ect on multimedia information retrieval.
Publication(s):
Probation review report carried out around 9 months after the start of doctoral work. Submitted 28/08/08
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...
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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