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Overell, Simon; Rae, Adam and Rüger, Stefan
(2009).
DOI: https://doi.org/10.1007/978-3-642-04447-2_109
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.
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About
- Item ORO ID
- 28212
- Item Type
- Conference or Workshop Item
- ISSN
- 0302-9743
- Extra Information
-
ISBN-13 978-3-642-04446-5
Pages 838-842 - Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2009 Springer-Verlag
- Depositing User
- Stefan Rüger