A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studies
In-text citation analysis is one of the most frequently used methods in research evaluation.
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
[PDF][PDF] Collaboro: a collaborative (meta) modeling tool
JLC Izquierdo, J Cabot - PeerJ Computer Science, 2016 - peerj.com
Motivation Scientists increasingly rely on intelligent information systems to help them in their
daily tasks, in particular for managing research objects, like publications or datasets. The …
daily tasks, in particular for managing research objects, like publications or datasets. The …
Machine learning vs. rules and out-of-the-box vs. retrained: An evaluation of open-source bibliographic reference and citation parsers
Bibliographic reference parsing refers to extracting machine-readable metadata, such as the
names of the authors, the title, or journal name, from bibliographic reference strings. Many …
names of the authors, the title, or journal name, from bibliographic reference strings. Many …
Semantic publishing challenge–assessing the quality of scientific output by information extraction and interlinking
Abstract The Semantic Publishing Challenge series aims at investigating novel approaches
for improving scholarly publishing using Linked Data technology. In 2014 we had …
for improving scholarly publishing using Linked Data technology. In 2014 we had …
New methods for metadata extraction from scientific literature
D Tkaczyk - arXiv preprint arXiv:1710.10201, 2017 - arxiv.org
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 …
communication to electronic media and also resulted in a substantial increase in its volume …
[PDF][PDF] Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge
While most challenges organized so far in the Semantic Web domain are focused on
comparing tools with respect to different criteria such as their features and competencies, or …
comparing tools with respect to different criteria such as their features and competencies, or …
CAD: An algorithm for citation-anchors detection in research papers
R Ahmad, MT Afzal - Scientometrics, 2018 - Springer
Citations are very important parameters and are used to take many important decisions like
ranking of researchers, institutions, countries, and to measure the relationship between …
ranking of researchers, institutions, countries, and to measure the relationship between …
[PDF][PDF] Evaluation and comparison of open source bibliographic reference parsers: A business use case
Bibliographic reference parsing refers to extracting machinereadable metadata, such as the
names of the authors, the title, or journal name, from bibliographic reference strings. Many …
names of the authors, the title, or journal name, from bibliographic reference strings. Many …
Parsrec: A novel meta-learning approach to recommending bibliographic reference parsers
Bibliographic reference parsers extract machine-readable metadata such as author names,
title, journal, and year from bibliographic reference strings. To extract the metadata, the …
title, journal, and year from bibliographic reference strings. To extract the metadata, the …
Semantic publishing challenge: bootstrapping a value chain for scientific data
The objective of the Semantic Publishing (SemPub) challenge series is to bootstrap a value
chain for scientific data to enable services, such as assessing the quality of scientific output …
chain for scientific data to enable services, such as assessing the quality of scientific output …