Probabilistic retrieval based on staged logistic regression
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Logistic regression for metadata: Cheshire takes on adhoc-TEL
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Probabilistic retrieval, component fusion and blind feedback for XML retrieval
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
CLEF 2008: ad hoc track overview
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Logistic regression for metadata: Cheshire takes on adhoc-TEL
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
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In this paper we will briefly describe the approaches taken by the Berkeley Cheshire Group for the Adhoc-TEL 2008 tasks (Mono and Bilingual retrieval). Since the Adhoc-TEL task is new for this year, we took the approach of using methods that have performed fairly well in other tasks. In particular, the approach this year used probabilistic text retrieval based on logistic regression and incorporating blind relevance feedback for all of the runs. All translation for bilingual tasks was performed using the LEC Power Translator PC-based MT system. This approach seems to be a fit good for the limited TEL records, since the overall results show Cheshire runs in the top five submitted runs for all languages and tasks except for Monolingual German.