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KMi Seminars
Improving Lucene's geographical data search performance with R-trees
This event took place on Friday 24 August 2007 at 12:00

 
Evgeny Shadchnev Imperial College London, Department of Computing

Lucene, a state-of-the-art open source information retrieval library, is an efficient solution for indexing and searching textual data. However, some Lucene usage scenarios require handling of geographically augmented data, that is, text documents that contain geographical coordinates (e.g. wikipedia pages about cities). This data is best searched using spacial access methods, such as R-trees, provided that the number of unique documents is large enough to benefit from this approach. An extension to Lucene that improves its speed at searching geographically augmented data is described.

 
KMi Seminars
 

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.