Find publications commonly cited by a group of papers, and more.
Specifically, it parses the data from Scopus via pybliometrics to
- Get the bibliography of an input paper.
- Find common references of all input papers.
- List the commonly cited ones, see if you miss some important papers.
- Sort papers by citation counts.
- Save metadata into markdown files for latter usage (e.g. paper notes).
It would be easier for researchers to start in a new area if they know the relationship (cross reference) and importance (citations) of a bunch of related papers.
- Make sure your institution has bought the database.
- Create a developer account at Scopus/Elsevier. You have 10000 requests/week as a free user.
- Install pybliometrics.
- Fill
./config/defaut_config.yaml
according to the instructions and runrun_citation_graph.py
in your institution network.
E.g., if I am interested in LiDAR loop closure detection and I find the DOIs of some papers, the sample output (please use full width terminal):