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Found 5 papers, 0 papers with code
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics.
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
Participation d'EDF R\&D \`a DEFT 2020 (This paper describes the participation of EDF R\&D at DEFT 2020 evaluation campaign)
Ce papier d{\'e}crit la participation d{'}EDF R{\&}D {\`a} la campagne d{'}{\'e}valuation DEFT 2020.
How to detect novelty in textual data streams? A comparative study of existing methods
Since datasets with annotation for novelty at the document and/or word level are not easily available, we present a simulation framework that allows us to create different textual datasets in which we control the way novelty occurs.
Participation d'EDF R\&D \`a DEFT 2018 (Here the title in English)
Aucune donn{\'e}e suppl{\'e}mentaire, autre que les donn{\'e}es d{'}apprentissage, n{'}a {\'e}t{\'e} utilis{\'e}e. Notre {\'e}quipe obtient des r{\'e}sultats tr{\`e}s corrects et se classe 1{\`e}re {\'e}quipe non acad{\'e}mique.
