Abstract
The baselines proposed for the ResPubliQA 2009 task are described in this paper. The main aim for designing these baselines was to test the performance of a pure Information Retrieval approach on this task. Two baselines were run for each of the eight languages of the task. Both baselines used the Okapi-BM25 ranking function, with and without a stemming. In this paper we extend the previous baselines comparing the BM25 model with Vector Space Model performance on this task. The results prove that BM25 outperforms VSM for all cases.
This work has been partially supported by the Spanish Ministry of Science and Innovation within the project QEAVis-Catiex (TIN2007-67581-C02-01), the TrebleCLEF Coordination Action, within FP7 of the European Commission, Theme ICT-1-4-1 Digital Libraries and Technology Enhanced Learning (Contract 215231), the Regional Government of Madrid under the Research Network MAVIR (S-0505/TIC-0267), the Education Council of the Regional Government of Madrid and the European Social Fund.
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Pérez-Iglesias, J., Garrido, G., Rodrigo, Á., Araujo, L., Peñas, A. (2010). Information Retrieval Baselines for the ResPubliQA Task. In: Peters, C., et al. Multilingual Information Access Evaluation I. Text Retrieval Experiments. CLEF 2009. Lecture Notes in Computer Science, vol 6241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15754-7_28
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DOI: https://doi.org/10.1007/978-3-642-15754-7_28
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