In the scope of project TRAINER, transfer learning methods applied to deep learning technologies for natural language processing tasks will be researched. The main goal of the project is the creation of a multilingual SaaS (software as a service) offer of natural language processing services that enables the internationalization of this Priberam’s business area.
The exponential growth of the volume of text content available, both inside and outside the organizations, is one of the main consequences of the digitization not only of the economy but also of an important part of the human activity, even not professional.
To extract value from all this text information available to the organizations, several software services are available to identify people, organizations, places and events mentioned in a text, link these entities to external knowledge bases, do sentiment analysis on posts in social media or summarize documents, only to give a few examples.
By integrating transfer learning methods in its SaaS offer of natural language processing services, Priberam will gain a clear advantage in regard to its competitors, as it will be able to reuse resources available in any specific language, to create services for languages where those resources are nonexistent.
Additionally, the project results will, in the future, be integrated in Priberam’s solutions for Media & Publishing, Media Intelligence, Legal Research and, in particular, Health, also contributing to the growth and internationalization of these business areas of the company.
Project name | TRAINER: Transfer Learning for Multilingual Natural Language Understanding
Project code | LISBOA-01-0247-FEDER-045347
Main goal | Reinforce the research, technological development and the innovation
Region | Lisbon
Beneficiary | Priberam Informática, S.A.
Approval date | 19-Dec-2019
Start date | 1-Jan-2020
End date | 31-Dec-2021
Total eligible cost | 568.169,57 EUR
European Union financial support | ERDF – 284.084,79 EUR