Abstract
In this paper we will briefly describe the approaches taken by Berkeley for the main GeoCLEF 2007 tasks (Mono and Bilingual retrieval). The approach this year was to use probabilistic text retrieval based on logistic regression and incorporating blind relevance feedback for all of the runs. Our intent was to establish a baseline result without explicit geographic processing for comparision with future geographic processing approaches. All translation for bilingual tasks was performed using the LEC Power Translator machine translation system.
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References
Chen, A.: Cross-Language Retrieval Experiments at CLEF 2002. In: Peters, C., Braschler, M., Gonzalo, J. (eds.) CLEF 2002. LNCS, vol. 2785, pp. 28–48. Springer, Heidelberg (2003)
LEC Power Translator 11 Premium, http://www.lec.com
Robertson, S.E., Sparck Jones, K.: Relevance weighting of search terms. Journal of the American Society for Information Science, 129–146 (May–June, 1976)
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Larson, R.R. (2008). Cheshire at GeoCLEF 2007: Retesting Text Retrieval Baselines. In: Peters, C., et al. Advances in Multilingual and Multimodal Information Retrieval. CLEF 2007. Lecture Notes in Computer Science, vol 5152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85760-0_102
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DOI: https://doi.org/10.1007/978-3-540-85760-0_102
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85759-4
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