Abstract. For our fifth participation in the CLEF evaluation campaigns, our first objective was to propose an effective and general stopword list as well as a light stemming procedure for the Hungarian, Bulgarian and Portuguese (Brazilian) languages. Our second objective was to obtain a better picture of the relative merit of various search engines when processing documents in those languages. To do so we evaluated our scheme using two probabilistic models and five vector-processing approaches. In the bilingual track, we evaluated both the machine translation and bilingual dictionary approaches applied to automatically translate a query submitted in English into various target languages. Finally, using the GIRT corpora (available in English, German and Russian), we investigated the variations in retrieval effectiveness that resulted when we included or excluded manually assigned keywords attached to the bibliographic records (mainly comprising a title and an abstract).

Abstract. In our fourth participation in the CLEF evaluation campaigns, our objective was to verify whether our combined query translation approach would work well with new requests and new languages (Russian and Portuguese in this case). As a second objective, we were to suggest a selection procedure able to extract a smaller number of documents from collections that seemed to contain no or only a few relevant items for the current request. We also applied different merging strategies in order to obtain more evidence about their respective relative merits.

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