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. © 2010 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Pérez-Iglesias, J., Garrido, G., Rodrigo, Á., Araujo, L., & Peñas, A. (2010). Information retrieval baselines for the ResPubliQA task. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6241 LNCS, pp. 253–256). https://doi.org/10.1007/978-3-642-15754-7_28
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
