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Abstract:This paper analyses three type of different indexing methods applied on French test collections (CLEF from 2000 to 2005): lemmas, truncated terms and single words. The same search engine and the same characteristics are used independently to the indexing method to avoid variability in the analysis. When evaluated on French CLEF collections, indexing by lemmas is the best method compared to single words and truncated term methods. We also analyse the impact of combining indexing methods by using the CombMNZ function. As CLEF topics are composed of different parts, we also examine the influence of these topic parts by comparing the results when topic parts are considered individually, and when they are combined. Finally, we combine both indexing methods and query parts. We show that MAP can be improved up to 8% compared to the best individual methods.

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