Abstract
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.
This work was supported by the Grant Agency of the Czech Academy of Sciences project No. 1ET101470416 and the Ministry of Education of the Czech Republic project No. LC536.
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Ircing, P., Müller, L. (2007). Benefit of Proper Language Processing for Czech Speech Retrieval in the CL-SR Task at CLEF 2006. In: Peters, C., et al. Evaluation of Multilingual and Multi-modal Information Retrieval. CLEF 2006. Lecture Notes in Computer Science, vol 4730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74999-8_95
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DOI: https://doi.org/10.1007/978-3-540-74999-8_95
Publisher Name: Springer, Berlin, Heidelberg
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