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 develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:
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Artificial Intelligence |
Nonlinear Time Series Analysis |
Web Research |
Music Technology |
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Interactive Technologies |
Barcelona MedTech |
Natural Language Processing |
Nonlinear Time Series Analysis |
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UbicaLab |
Wireless Networking |
Educational Technologies |
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.
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