Abstract
In this paper, we present two different question-answering systems on speech transcripts which participated to the QAst 2007 evaluation. These two systems are based on a complete and multi-level analysis of both queries and documents. The first system uses handcrafted rules for small text fragments (snippet) selection and answer extraction. The second one replaces the handcrafting with an automatically generated research descriptor. A score based on those descriptors is used to select documents and snippets. The extraction and scoring of candidate answers is based on proximity measurements within the research descriptor elements and a number of secondary factors. The evaluation results are ranged from 17% to 39% as accuracy depending on the tasks.
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Rosset, S., Galibert, O., Adda, G., Bilinski, E. (2008). The LIMSI Participation in the QAst Track. In: Peters, C., et al. Advances in Multilingual and Multimodal Information Retrieval. CLEF 2007. Lecture Notes in Computer Science, vol 5152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85760-0_55
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DOI: https://doi.org/10.1007/978-3-540-85760-0_55
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