Logistic Regression for Metadata: Cheshire Takes on Adhoc-TEL

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 AdhocTEL 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. Categories and Subject Descriptors H.3 [Information Storage and Retrieval]: H.3.1 Content Analysis and Indexing; H.3.3 Information Search and Retrieval General Terms Algorithms, Performance, Measurement Keywords Cheshire II, Logistic Regression

• Type: Conference
• Year: 2008
• Where: CLEF
• Authors: Ray R. Larson
• Keywords: Adhoc-TEL 2008 Tasks, CLEF 2008, Information Management, Logistic Regression, Probabilistic Text Retrieval