Abstract
Citation graphs visualize citation relationships of publications. Hence citation graphs enable in-depth analysis about the impact of publications to research areas, such that citation graphs have great benefits for systematic reviews about a special field of research. In this contribution, we introduce a tool for automatically generating citation graphs from a set of paper documents, which runs stand-alone or integrated in a systematic reviews application. As systematic reviews often include many papers, we also propose several strategies to reduce the complexity of citation graphs and add additional information for in-depth analysis of the impact of single publications. In addition to citation graphs our tool also visualizes the publication selection process of systematic reviews. The generated graphs and developed strategies are evaluated using different instruments, including an user
survey, in which they are rated positively.
survey, in which they are rated positively.
| Original language | English |
|---|---|
| Journal | Open J. Inf. Syst. |
| Volume | 8 |
| Issue number | 1 |
| Pages (from-to) | 1-25 |
| Publication status | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 4 Quality Education -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 12 Responsible Consumption and Production -
SDG 14 Life Below Water -
SDG 15 Life on Land
Research Areas and Centers
- Research Area: Intelligent Systems
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
DFG Research Classification Scheme
- 4.43-03 Security and Dependability, Operating, Communication and Distributed Systems
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