Abstract
We present in this paper the three LIMSI question-answering systems on speech transcripts which participated to the QAst 2009 evaluation. These systems are based on a complete and multi-level analysis of both queries and documents. These systems use an automatically generated research descriptor. A score based on those descriptors is used to select documents and snippets. Three different methods are tried to extract and score candidate answers, and we present in particular a tree transformation based ranking method. We participated to all the tasks and submitted 30 runs (for 24 sub-tasks). The evaluation results for manual transcripts range from 27% to 36% for accuracy depending on the task and from 20% to 29% for automatic transcripts. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Bernard, G., Rosset, S., Galibert, O., Adda, G., & Bilinski, E. (2010). The LIMSI participation in the QAst 2009 track: Experimenting on answer scoring. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6241 LNCS, pp. 289–296). https://doi.org/10.1007/978-3-642-15754-7_33
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