UniNE at Domain-Specific IR - CLEF 2008

Our first objective in participating in this domain-specific evaluation campaign is to propose and evaluate various indexing and search strategies for the German, English and Russian languages, in an effort to obtain better retrieval effectiveness than that of the language-independent approach (n-gram). To do so we evaluate the GIRT-4 test-collection using the Okapi, various IR models derived from the Divergence from Randomness (DFR) paradigm, the statistical language model (LM) together with the classical tf.idf vector-processing scheme. Categories and Subject Descriptors H.3.1 [Content Analysis and Indexing]: Indexing methods, Linguistic processing. I.2.7 [Natural Language Processing]: Language models. H.3.3 [Information Storage and Retrieval]: Retrieval models. H.3.4 [Systems and Software]: Performance evaluation. General Terms Experimentation, Performance, Measurement, Algorithms. Additional Keywords and Phrases Natural Language Processing with European Languages, Digital Librarie...

• Type: Conference
• Year: 2008
• Where: CLEF
• Authors: Claire Fautsch, Ljiljana Dolamic, Jacques Savoy
• Keywords: CLEF 2008, Information Management, Language Models, Natural Language Processing, Russian Language