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Poperty graphs modelling in neo4j and Python. Team project from UPC's Master's Degree in Data Science

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airdac/SDM-Property_Graphs

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SDM-Property_Graphs

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

  1. Update it and transform the model
  2. Query the graph data
  3. Create a recommender
  4. Process graph data with traditional graph metrics / algorithms