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 ...
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).
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