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Domain-Specific IR for German, English and Russian Languages

Auteur(s)
Fautsch, Claire
Editeur(s)
Dolamic, Ljiljana
Abdou, Samir
Savoy, Jacques 
Institut d'informatique 
Date de parution
2008
In
Lecture Notes in Computer Science (LNCS), Springer, 2008/5152//196-199
Résumé
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 <i>tf •idf</i>, Okapi, IR models derived from the <i>Divergence from Randomness</i> (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.
URI
https://libra.unine.ch/handle/123456789/14382
DOI
10.1007/978-3-540-85760-0_26
Autre version
http://dx.doi.org/10.1007/978-3-540-85760-0_26
Type de publication
Resource Types::text::journal::journal article
Dossier(s) à télécharger
 main article: Fautsch_Claire_-_Domain-Specific_IR_for_German_English_and_Russian_20100211.pdf (405.3 KB)
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