Large scale subject category classification of scholarly papers with Deep Attentive Neural Networks
Subject categories of scholarly papers generally refer to the knowledge domain (s) to which
the papers belong, examples being computer science or physics. Subject category …
the papers belong, examples being computer science or physics. Subject category …
Fast and scalable neural embedding models for biomedical sentence classification
Background Biomedical literature is expanding rapidly, and tools that help locate information
of interest are needed. To this end, a multitude of different approaches for classifying …
of interest are needed. To this end, a multitude of different approaches for classifying …
Comparing paper level classifications across different methods and systems: an investigation of Nature publications
The classification of scientific literature into appropriate disciplines is an essential
precondition of valid scientometric analysis and significant to the practice of research …
precondition of valid scientometric analysis and significant to the practice of research …
A model for the identification of the functional structures of unstructured abstracts in the social sciences
S Shen, C Jiang, H Hu, Y Ji, D Wang - The Electronic Library, 2022 - emerald.com
Purpose Reorganising unstructured academic abstracts according to a certain logical
structure can help scholars not only extract valid information quickly but also facilitate the …
structure can help scholars not only extract valid information quickly but also facilitate the …
Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature
S Zhou, X Li - Information Processing & Management, 2020 - Elsevier
Section identification is an important task for library science, especially knowledge
management. Identifying the sections of a paper would help filter noise in entity and relation …
management. Identifying the sections of a paper would help filter noise in entity and relation …
Which structure of academic articles do referees pay more attention to?: perspective of peer review and full-text of academic articles
C Qin, C Zhang - Aslib Journal of Information Management, 2023 - emerald.com
Purpose The purpose of this paper is to explore which structures of academic articles
referees would pay more attention to, what specific content referees focus on, and whether …
referees would pay more attention to, what specific content referees focus on, and whether …
Discovering IMRaD structure with different classifiers
Information within published papers around the world in scientific journals are structured in
the format of Introduction, Methodology, Results, and Conclusion (IMRaD). Human ability to …
the format of Introduction, Methodology, Results, and Conclusion (IMRaD). Human ability to …
Structured fine-tuning of contextual embeddings for effective biomedical retrieval
Biomedical literature retrieval has greatly benefited from recent advances in neural
language modeling. In particular, fine-tuning pretrained contextual language models has …
language modeling. In particular, fine-tuning pretrained contextual language models has …
ResGAT: an improved graph neural network based on multi-head attention mechanism and residual network for paper classification
X Huang, Z Wu, G Wang, Z Li, Y Luo, X Wu - Scientometrics, 2024 - Springer
Paper classification plays a pivotal role in facilitating precise literature retrieval,
recommendations, and bibliometric analyses. However, current text-based methods …
recommendations, and bibliometric analyses. However, current text-based methods …
EMAKG: An enhanced version of the microsoft academic knowledge graph
L Pollacci - arXiv preprint arXiv:2203.09159, 2022 - arxiv.org
Scholarly knowledge graphs are valuable sources of information in several research fields.
Despite the number of existing datasets related to publications and researchers, resource …
Despite the number of existing datasets related to publications and researchers, resource …