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Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning
Comparing Named-Entity Recognizers in a Targeted Domain : Handcrafted Rules vs. Machine Learning Named-Entity Recognition concerns the classification of textual objects in a predefined set of categories such as persons, organizations, and localizations.
Encoding Adjective Scales for Fine-grained Resources
We propose an automatic approach towards determining the relative location of adjectives on a common scale based on their strength.
Un syst\`eme expert fond\'e sur une analyse s\'emantique pour l'identification de menaces d'ordre biologique
Le projet europ{\'e}en TIER (Integrated strategy for CBRN {--} Chemical, Biological, Radiological and Nuclear {--} Threat Identification and Emergency Response) vise {\`a} int{\'e}grer une strat{\'e}gie compl{\`e}te et int{\'e}gr{\'e}e pour la r{\'e}ponse d{'}urgence dans un contexte de dangers biologiques, chimiques, radiologiques, nucl{\'e}aires, ou li{\'e}s aux explosifs, bas{\'e}e sur l{'}identification des menaces et d{'}{\'e}valuation des risques.
Generating a Resource for Products and Brandnames Recognition. Application to the Cosmetic Domain.
Named Entity Recognition task needs high-quality and large-scale resources.
