Saggion H, Ronzano F, Accuosto P,  Ferrés D. MultiScien: a Bi-Lingual Natural Language Processing System for Mining and Enrichment of Scientific Collections. 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017), at SIGIR 2017

In the current online Open Science context, scientific datasets and tools for deep text analysis, visualization and exploitation play a major role. We present a system for deep analysis and annotation of scientific text collections. We also introduce the first version of the SEPLN Anthology, a bi-lingual (Spanish and English) fully annotated text resource in the field of natural language processing that we created with our system. Moreover, a faceted-search and visualization system to explore the created resource is introduced. All resources created for this paper will be available to the research community.

Additional material:

• Post-print at UPF repository
• Dataset: annotated textual contents of the SEPLN Anthology
• Dr. Inventor Text Mining Framework