Faculté des sciences

Domain-Specific IR for German, English and Russian Languages

Fautsch, Claire ; Dolamic, Ljiljana ; Abdou, Samir ; Savoy, Jacques

In: Lecture Notes in Computer Science (LNCS), 2008, vol. 5152, p. 196-199

In participating in this domain-specific track, our first objective is to propose and evaluate a light stemmer for the Russian language. Our second objective is to measure the relative merit of various search engines used for the German and to a lesser extent the English languages. To do so we evaluated the tf •idf, Okapi, IR models derived from the Divergence from Randomness... Plus

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    Summary
    In participating in this domain-specific track, our first objective is to propose and evaluate a light stemmer for the Russian language. Our second objective is to measure the relative merit of various search engines used for the German and to a lesser extent the English languages. To do so we evaluated the tf •idf, Okapi, IR models derived from the Divergence from Randomness (DFR) paradigm, and also a language model (LM). For the Russian language, we find that word-based indexing using our light stemming procedure results in better retrieval effectiveness than does the 4-gram indexing strategy (relative difference around 30%). Using the German corpus, we examine certain variations in retrieval effectiveness after applying the specialized thesaurus to automatically enlarge topic descriptions. In this case, the performance variations were relatively small and usually non significant.