NIPS 2006
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Machine Learning for Multilingual Information Access

Cyril Goutte


With increasing pressure for accessing, understanding and translating information available in different languages, Machine Learning has the potential to provide much needed technology for multilingual applications. However, there are also specific issues and pitfalls, such as the need to work with limited resources, to integrate prior linguistic knowledge, to scale up to very large text corpora, and to provide evaluation measures that correspond to human assessments. This workshop will provide the opportunity for researchers interested in Machine Learning and/or Computational Linguistics to analyse and discuss challenges in applying ML to multilingual information access, possible solutions, and existing applications.

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