In last few decades, with the advent of World Wide Web (WWW), world is being overloaded
with huge data. This huge data carries potential information that once extracted, can be used …

Extracting the body text from a PDF document is an important but surprisingly difficult task.
The reason is that PDF is a layout-based format which specifies the fonts and positions of …

We present a deep learning approach for the core digital libraries task of parsing
bibliographic reference strings. We deploy the state-of-the-art long short-term memory …

The present article aims to review and evaluate the practiced and classical techniques,
tools, models, and systems concerning automatic information extraction (IE) from published …

Within the past few decades we have witnessed digital revolution, which moved scholarly
communication to electronic media and also resulted in a substantial increase in its volume …

In this paper, we compare the performance of several popular pre-trained reference
extraction and segmentation toolkits combined in different pipeline configurations on three …

Bibliographic reference parsers extract machine-readable metadata such as author names,
title, journal, and year from bibliographic reference strings. To extract the metadata, the …

Metadata such as bibliographic information about documents are indispensable in the
effective use of digital libraries. In particular, the reference fields of academic papers contain …

Large-scale pre-trained models such as GPT and BERT have demonstrated remarkable
performance in information extraction tasks. However, their black-box nature poses …

Citation parsing is fundamental for search engines within academia and the protection of
intellectual property. Meticulous extraction is further needed when evaluating the similarity of …