Ronzano F, Freire A, Saez-Trumper D, Saggion H. Making sense of massive amounts of scientific publications: the scientific knowledge miner project. Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016)
We have relevant datasets, repositories, frameworks and tools of relevance for research and technology transfer initiatives related to knowledge extraction. This section provides an overview on a selection of them and links to download or contact details.
The MdM Strategic Research Program has its own community in Zenodo for material available in this repository
as well as at the UPF e-repository 
. Below a non-exhaustive list of datasets representative of the research in the Department.
As part of the promotion of the availability of resources, the creation of specific communities in Zenodo has also been promoted, at level of research communities (for instance, MIR and Educational Data Analytics) or MSc programs (for instance, the Master in Sound and Music Computing)
Ronzano F, Freire A, Saez-Trumper D, Saggion H. Making sense of massive amounts of scientific publications: the scientific knowledge miner project. Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016)
Ronzano F, Freire A, Saez-Trumper D, Saggion H. Making sense of massive amounts of scientific publications: the scientific knowledge miner project. Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016). CEUR workshop Proceedings.
The World Wide Web has become the hugest repository ever for scientific publications and it continues to increase at an unprecedented rate. Nevertheless, this information overload makes the exploration of this content a very time-consuming task. In this landscape, the availability of text mining tools to characterize and explore distinctive features of the scientific literature is mandatory. We present the Scientific Knowledge Miner (SKM) Project, that aims to investigate new approaches and frameworks to facilitate the extraction of knowledge from scientific publications across different disciplines. More specifically, we will focus on citation characterization, recommendation and scientific document summarization.
Additional material: