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
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Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
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