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PG2Net: Personalized and Group PreferenceGuided Network for Next Place Prediction

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PG2Net

PG2Net:Personalized and Group Preference Guided Network for Next Place Prediction

Datasets

Experiment results on two Foursquare check-in datasets [NYC,TKY] and one mobile phone dataset [CDRs]

Requirements

  • Python 3.6+
  • Pytorch 1.4+

Project Structure

  • baselines
  • codes
    • main.py # setting parameters
    • train.py # train model
    • model.py # define models
    • utils.py # define tools

Usage

  • The "distance.pkl" is generated by the "caculate_poi_distance" function in the "utils.py".
  • The "cid_time.pkl" is generated by the "caculate_time_cid" function in the "utils.py".
  • The "loc.emb" and "cid.emb" are generated by the "construc_graph" function in the "utils.py" and Node2vec.
  • Train model #python main.py

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PG2Net: Personalized and Group PreferenceGuided Network for Next Place Prediction

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  • Python 100.0%