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Multi-Objective Data Discovery

Pre Processing

  • Constructing Universal Schema: Utils/schema.py -> XXX_filtered.csv

  • Clustering tables to get adom with size bounded -> clustered_table.csv

  • Constructing Graph (if need): Utils/graph_igraph_table.py -> nodes.csv, edges.csv

  • Surrogate model:

    • Sample Nodes and get real training results: Utils/sample_nodes.py -> sampled_nodes.csv

    • Train surrogate model: Surrogate/XXX_surrogate_model.py -> XXX_surrogate.joblib

Data Discovery

  • ApxMODis: Algorithms/si_direct.py

  • BiMODis:

    • Build orrelation graph: Utils/correlation_analysis.py -> correlation_graph.csv

    • Run BiMODis: Algorithms/bi_direct_corr.py

    • BiMODis without correlation graph: Algorithms/bi_direct.py

  • DivMODis: Algorithms/divmodis.py

  • IncMODis: Algorithms/incmodis.py

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