Ranking Refinement via Relevance Feedback in Geographic Information Retrieval
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Cheshire at GeoCLEF 2008: text and fusion approaches for GIR
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Multilingual query expansion for CLEF Adhoc-TEL
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Interactive probabilistic search for GikiCLEF
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Decomposing text processing for retrieval: Cheshire tries GRID@CLEF
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
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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.