• Aucun résultat trouvé

Organisation

N/A
N/A
Protected

Academic year: 2022

Partager "Organisation"

Copied!
1
0
0

Texte intégral

(1)

Organisation

Workshop Chair:

Tamas Kiss, University of Westminster, UK

Local Organisation:

Gabor Terstyanszky, University of Westminster, UK Noam Weingarten, University of Westminster, UK

Program Committee:

Roberto Barbera, University of Catania and INFN, Italy Stephen Brewer, EGI.eu, Amsterdam, The Netherlands Denis Caromel, INRIA, Sophia Antipolis, France Thierry Delaitre, University of Westminster, UK Sandra Gesing, University of Tübingen, Germany Tristan Glatard, CNRS CREATIS, Lyon, France Peter Kacsuk, MTA SZTAKI, Budapest, Hungary Tamas Kiss, University of Westminster, UK

Oliver Kohlbacher, University of Tübingen, Germany Miklos Kozlovszky, MTA SZTAKI, Budapest, Hungary Dagmar Krefting, Charite, Berlin, Germany

Peter Kunszt, ETH, SystemsX.ch, Zürich, Switzerland

Luciano Milanesi, Institute of Biomedical Technologies, Milan, Italy Johan Montagnat, CNRS, France

Jarek Nabrzyski, University of Notre Dame, Indiana, US

Silvia Delgado Olabarriaga, Academic Medical Centre, Amsterdam, The Netherlands Richard Sinnott, University of Melbourne, Australia

Gergely Sipos, EGI.eu, Amsterdam, The Netherlands Simon Taylor, Brunel University, London, UK Gabor Terstyanszky, University of Westminster, UK Dawid Szejnfeld, PSNC Poznan, Poland

Eric Yen, Academia Sinica Grid Computing Center, Taipei, Taiwan Nancy Wilkins-Diehr, SDSC, San Diego, US

Stephen Winter, University of Westminster, UK

Références

Documents relatifs

Given a topic (and associated article) in one language, identify relevant snippets on the topic from other articles in the same language or even in other languages.. In the context

Language restricted Since we know the language of the topic in each of the translations, and the intention of the translated topic is to retrieve pages in that language, we may

When we examined the assessments of the answers to the three different question types, we noticed that the proportion of correct answers was the same for definition questions (45%)

For both English and Portuguese we used a similar set of indexes as for the monolingual runs described earlier (Words, Stems, 4-Grams, 4-Grams+start/end, 4-Grams+words); for all

Four streams generate candidate answers from the Dutch CLEF corpus: Lookup, Pattern Match, Ngrams, and Tequesta.. The Table Lookup stream uses specialized knowledge bases constructed

In effect, we conducted three sets of experiments: (i) on the four language small multilingual set (English, French, German, and Spanish), (ii) on the six languages for which we have

The Web Answer stream, for example, seemed to perform better than other streams on questions for which the answer was a date; the Pattern and Table Lookup streams had very

As to the effect of stemming on retrieval performance for languages that are morphologically richer than English, such as Dutch, German, or Italian, in our experiments for CLEF 2001