Multi-level mining and visualization of scientific text collections

Comunicació presentada a: 6th International Workshop on Mining Scientific Publications (WOSP 2017), celebrat el 19 de juny a Toronto, Canada. We present a system to mine and visualize collections of scientific documents by semantically browsing information extracted from single publications or aggregated throughout corpora of articles. The text mining tool performs deep analysis of document collections allowing the extraction and interpretation of research paper’s contents. In addition to the extraction and enrichment of documents with metadata (titles, authors, affiliations, etc), the deep analysis performed comprises semantic interpretation, rhetorical analysis of sentences, triple-based information extraction, and text summarization. The visualization components allow geographicalbased exploration of collections, topic-evolution interpretation, and collaborative network analysis among others. The paper presents a case study of a bilingual collection in the field of Natural Language Processing (NLP). This work is (partly) supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and by the TUNER project (TIN2015- 65308-C5-5-R, MINECO/FEDER, UE).