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KMi Seminars
Off the beaten track: using content-based multimedia similarity search for learning
This event took place on Friday 04 March 2011 at 11:30

Suzanne Little

Electronic media is a valuable and ever increasing resource for information seekers and learners. So much information can be contained in a picture, explained by a diagram or demonstrated in a video clip. But how can you find what you are looking for if you don't understand it well enough to describe it? What can you do if you are faced with a mountain of multimedia learning material? Are there other ways of exploring open educational resources then sticking to the well defined paths of text search and hyperlinks?

This talk will present recent work applying content-based multimedia similarity search to find related educational material by using images to query a collection. It will describe the use of local features in images, 'keypoints', identified using an approach called Scale-Invariant Feature Transforms (SIFT) [1], and the implementation of a nearest neighbour based indexing system to find visually similar images. The resulting content-based media search tool (cbms) has been applied in the context of the SocialLearn project [2] to help users find and explore connected web pages, presentations or documents. It is also the basis of the Spot&Search [3] iPhone application that can be used to explore artwork installations on the OU Walton Hall campus.

[1] http://www.cs.ubc.ca/~lowe/keypoints/
[2] http://www.sociallearn.org
[3] http://spotandsearch.kmi.open.ac.uk

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Semantic Web and Knowledge Services is...


Semantic Web and Knowledge Services
"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" (Berners-Lee et al., 2001).

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...

Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.