The paper describes the system built by the team from the University of West Bohemia for participation in the CLEF 2006 CL-SR track. We have decided to concentrate only on the monolingual searching in the Czech test collection and investigate the effect of proper language processing on the retrieval performance. We have employed the Czech morphological analyser and tagger for that purposes. For the actual search system, we have used the classical tf.idf approach with blind relevance feedback as implemented in the Lemur toolkit. The results indicate that a suitable linguistic preprocessing is indeed crucial for the Czech IR performance. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Ircing, P., & Müller, L. (2007). Benefit of proper language processing for Czech speech retrieval in the CL-SR task at CLEF 2006. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4730 LNCS, pp. 759–765). Springer Verlag. https://doi.org/10.1007/978-3-540-74999-8_95
Mendeley helps you to discover research relevant for your work.