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.
This event took place on Friday 24 August 2007 at 12:00
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.
Future Internet
KnowledgeManagementMultimedia &
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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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