  Scientific digital libraries play a critical role in the development and
dissemination of scientific literature. Despite dedicated search engines,
retrieving relevant publications from the ever-growing body of scientific
literature remains challenging and time-consuming. Indexing scientific articles
is indeed a difficult matter, and current models solely rely on a small portion
of the articles (title and abstract) and on author-assigned keyphrases when
available. This results in a frustratingly limited access to scientific
knowledge. The goal of the DELICES project is to address this pitfall by
exploiting semantic relations between scientific articles to both improve and
enrich indexing. To this end, we will rely on the latest advances in semantic
representations to both increase the relevance of keyphrases extracted from the
documents, and extend indexing to new terms borrowed from semantically similar
documents.
