The Sustainable Development Goals (SDGs) are the guiding line to achieve a better and more sustainable future for all. They tackle the global challenges we face, including poverty, inequality, climate change, environmental degradation, peace and justice. The OnePlanet network - an open partnership for sustainable development - provides a platform where all countries, including all relevant stakeholders and organizations, are invited to join and actively engage. Thus, the latter submit daily a large number of descriptions of innovative projects that may be linked to one or more SDGs. For experts, the task of linking all the texts submitted to the SDGs they deal with is very time consuming, which is why the need to automate this process is very important. In this context, we propose to solve this problem with a multi-lablel classification of texts using BERT (Bidirectional Encoder Representations from Transformers). We first present the key steps for building our database, then the multi-label classification phase using BERT and finally we will present and discuss the obtained results.
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