Abstract
During this CLEF evaluation campaign, the first objective is to propose and evaluate various indexing and search strategies for the Czech language that will hopefully result in more effective retrieval than language-independent approaches (n-gram). Based on the stemming strategy we developed for other languages, we propose that for the Slavic language a light stemmer (inflectional only) and also a second one based on a more aggressive suffix-stripping scheme that will remove some derivational suffixes. Our second objective is to undertake further study of the relative merit of various search engines when exploring Hungarian and Bulgarian documents. To evaluate these solutions we use various effective IR models. Our experiments generally show that for the Bulgarian language, removing certain frequently used derivational suffixes may improve mean average precision. For the Hungarian corpus, applying an automatic decompounding procedure improves the MAP. For the Czech language a comparison of a light and a more aggressive stemmer to remove both inflectional and some derivational suffixes, reveals only small performance differences. For this language only, performance differences between a word-based or a 4-gram indexing strategy are also rather small.KeywordsAverage PrecisionRetrieval PerformanceMean Average PrecisionIndexing StrategyStopword ListThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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