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The InFile project (INformation, FILtering, Evaluation) is a cross-language adaptive filtering evaluation campaign, sponsored by the French National Research Agency. The campaign is organized by the CEA LIST, ELDA and the University of Lille3-GERiiCO. It has an international scope as it is a pilot track of the CLEF 2008 campaigns. The corpus is built from a(More)
In this paper, we report on the results of a full-size evaluation campaign of various MT systems. This campaign is novel compared to the classical DARPA/NIST MT evaluation campaigns in the sense that French is the target language, and that it includes an experiment of meta-evaluation of various metrics claiming to better predict different attributes of(More)
In a previous study (Dabbadie, Mustafa, Timimi, 2001) we set a methodology for non interactive machine translation evaluation on big corpora, assuming that the goal of the translation was a simple understanding of the original message. The source text, in French, provided by INRA (Institut National pour la Recherche Agronomique i.e. National Institute for(More)
In this study, we are concerned by a field which represents an intellectual, social, and economic practice, strongly linked to a semi-automatic knowledge organization. lnformational Competitive lntelligence is characterized by two major distinctive features: transition from the classical activity of Information Retrieval to organised lnformation Filtering,(More)
The INFILE@CLEF 2009 track is the second run of this track on the evaluation of cross-language adaptive filtering systems. It uses the same corpus as the 2008 track, composed of 300,000 newswires from Agence France Presse (AFP) in three languages: Arabic, English and French, and a set of 50 topics in general and specific domain (scientific and technological(More)
This paper describes the ongoing evaluation work in CESART research project supported by the French Ministry of Research and Technology 1 and coordinated by the University of Lille 3 and ELDA. The project deals with the evaluation of term and semantic relation extraction from corpora in French. CESART logically follows on the evaluation project achieved(More)
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