In this project we have been asked to model academic papers, journals, conferences and authors data as a graph in neo4j.
We start by getting data from DBLP. Then we preprocess and load it to a neo4j database through Python, with pandas and the neo4j modules.
Once our data is loaded, we are expected to
- Update it and transform the model
- Query the graph data
- Create a recommender
- Process graph data with traditional graph metrics / algorithms