most citedDomain-independent Extraction of Scientific Concepts from Research Articles

54 citations · 73 across the 5 of their papers we have counts for

collaborators

7 papers

cs.DL2021

Citation Recommendation for Research Papers via Knowledge Graphs

Arthur Brack, Anett Hoppe, Ralph Ewerth

Citation recommendation for research papers is a valuable task that can help researchers improve the quality of their work by suggesting relevant related work. Current approaches f…

cs.DL2021★ 1 cited

Analysing the Requirements for an Open Research Knowledge Graph: Use Cases, Quality Requirements and Construction Strategies

Arthur Brack, Anett Hoppe, Markus Stocker +2

Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it…

cs.CL2021

Cross-Domain Multi-Task Learning for Sequential Sentence Classification in Research Papers

Arthur Brack, Anett Hoppe, Pascal Buschermöhle +1

Sequential sentence classification deals with the categorisation of sentences based on their content and context. Applied to scientific texts, it enables the automatic structuring…

cs.IR2021

Coreference Resolution in Research Papers from Multiple Domains

Arthur Brack, Daniel Uwe Müller, Anett Hoppe +1

Coreference resolution is essential for automatic text understanding to facilitate high-level information retrieval tasks such as text summarisation or question answering. Previous…

cs.DL2020★ 12 cited

Requirements Analysis for an Open Research Knowledge Graph

Arthur Brack, Anett Hoppe, Markus Stocker +2

Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it…

cs.IR2020★ 6 cited

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…