Geographic and textual data fusion in Forostar

Authors:
Simon Overell;Adam Rae;Stefan Rüger
Affiliations:
Department of Computing, Imperial College London, London, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK and Department of Computing, Imperial College London, London, UK
Venue:
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Year:
2008

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Abstract

In this paper we provide some analysis of data fusion techniques employed at GeoCLEF 2008 to merge textual and geographic relevance. These methods are compared to our own experiments, where using our GIR system, Forostar, we show that an aggressive filter-based data fusion method can outperform a more sophisticated penalisation method.