Domain-Specific IR for German, English and Russian Languages

In participating in this CLEF evaluation campaign, our first objective is to propose and evaluate various indexing and search strategies for the Russian language, in order to obtain better retrieval effectiveness than that provided by the language-independent approach (n-gram). Our second objective is to more effectively measure the relative merit of various search engines when used for the German and to a lesser extent the English language. 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. We also evaluated different pseudo-relevance feedback approaches. For the Russian language, we find that word-based indexing with our light stemming procedure results in better retrieval effectiveness than does 4-gram indexing strategy (relative difference around 30%). Using the GIRT corpora (available in German...

• Type: Conference
• Year: 2007
• Where: CLEF
• Authors: Claire Fautsch, Ljiljana Dolamic, Samir Abdou, Jacques Savoy
• Keywords: Better Retrieval Effectiveness, CLEF 2007, Information Retrieval, Retrieval Effectiveness, Russian Language