  This paper proposes OCR++, an open-source framework designed for a variety of
information extraction tasks from scholarly articles including metadata (title,
author names, affiliation and e-mail), structure (section headings and body
text, table and figure headings, URLs and footnotes) and bibliography (citation
instances and references). We analyze a diverse set of scientific articles
written in English language to understand generic writing patterns and
formulate rules to develop this hybrid framework. Extensive evaluations show
that the proposed framework outperforms the existing state-of-the-art tools
with huge margin in structural information extraction along with improved
performance in metadata and bibliography extraction tasks, both in terms of
accuracy (around 50% improvement) and processing time (around 52% improvement).
A user experience study conducted with the help of 30 researchers reveals that
the researchers found this system to be very helpful. As an additional
objective, we discuss two novel use cases including automatically extracting
links to public datasets from the proceedings, which would further accelerate
the advancement in digital libraries. The result of the framework can be
exported as a whole into structured TEI-encoded documents. Our framework is
accessible online at http://cnergres.iitkgp.ac.in/OCR++/home/.
