Cheshire at GeoCLEF 2008: Text and Fusion Approaches for GIR

In this paper we will briefly describe the approaches taken by Berkeley for the main GeoCLEF 2008 tasks (Mono and Bilingual retrieval). The approach this year used probabilistic text retrieval based on logistic regression and incorporating blind relevance feedback for all of the runs and in addition we ran a number of tests combining this type of search with OKAPI BM25 searches using a fusion approach. All translation for bilingual tasks was performed using the LEC Power Translator PC-based MT system. Our results were good overall with Cheshire systems runs appearing in the top 5 participants for each task (German, English and Portuguese both Monolingual and Bilingual) with the highest ranked runs for Monolingual Portuguese and for Bilingual German, English and Portuguese. All of these top-ranked runs used the fusion approach. However, once again this year we did not attempt to do any specialized geographic processing, because it appears that purely textual approaches to GIR are more ...

• Type: Conference
• Year: 2008
• Where: CLEF
• Authors: Ray R. Larson
• Keywords: Bilingual Retrieval, CLEF 2008, Fusion Approach, Information Management, Logistic Regression