Description
Date depot: 1 janvier 1900
Titre: Knowledge extraction in web media: at the frontier of NLP, Machine Learning and Semantics
Encadrant :
Raphael TRONCY (Eurecom)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
The Web offers a vast amount of structured and unstructured content from which more and more advanced techniques are developed for extracting entities and relations between entities,
one of the key elements for feeding the various knowledge graphs that are being developed by major web companies as part of their product offerings. Most of the knowledge available on the
Web is present as natural language text enclosed in Web documents aimed at human consumption. A common approach for obtaining programmatic access to such a knowledge uses information extraction techniques. It reduces texts written in natural languages to machine readable structures, from which it is possible to retrieve entities and relations, for instance
obtaining answers to databasestyle queries. In the series of the WoLE workshops ([1] and [2]), we have proposed and discussed such a vision, gaining in popularity and attracting high quality
papers. We contributed to the emerging idea that entities should be a first class citizen on the Web.
Doctorant.e: Plu Julien