54 citations · 100 across the 12 of their papers we have counts for
6 papers · 1 filter
SciBERT-based Semantification of Bioassays in the Open Research Knowledge Graph
Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos +1
As a novel contribution to the problem of semantifying biological assays, in this paper, we propose a neural-network-based approach to automatically semantify, thereby structure, u…
Representing Semantified Biological Assays in the Open Research Knowledge Graph
Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos +1
In the biotechnology and biomedical domains, recent text mining efforts advocate for machine-interpretable, and preferably, semantified, documentation formats of laboratory process…
NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing Literature
Jennifer D'Souza, Sören Auer
We describe an annotation initiative to capture the scholarly contributions in natural language processing (NLP) articles, particularly, for the articles that discuss machine learn…
Improving Scholarly Knowledge Representation: Evaluating BERT-based Models for Scientific Relation Classification
Ming Jiang, Jennifer D'Souza, Sören Auer +1
With the rapid growth of research publications, there is a vast amount of scholarly knowledge that needs to be organized in digital libraries. To deal with this challenge, techniqu…
The STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources
Jennifer D'Souza, Anett Hoppe, Arthur Brack +3
We introduce the STEM (Science, Technology, Engineering, and Medicine) Dataset for Scientific Entity Extraction, Classification, and Resolution, version 1.0 (STEM-ECR v1.0). The ST…
Domain-independent Extraction of Scientific Concepts from Research Articles
Arthur Brack, Jennifer D'Souza, Anett Hoppe +2
We examine the novel task of domain-independent scientific concept extraction from abstracts of scholarly articles and present two contributions. First, we suggest a set of generic…