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DeepApp

This is the code for submission 1833 in CIKM2019

Datasets

The sample data to evaluate our model, which contains 1000 users and ready for directly used.

Requirements

  • Python 2.7
  • Pytorch 0.20
  • cPickle is used in the project to store the preprocessed data and parameters.

Project Structure

  • /data # preprocessed sample data (pickle file)
  • /codes
    • main.py
    • model.py # define models
    • train.py # define tools for train the model
  • /baseline #codes for baseline App2Vec
    • main.py
    • model.py # define models
    • train.py # define tools for train the model

Usage

python main.py --users_end 1000 --model_mode AppPreLocPreUserIdenGtr --lr_step 1 --process_name user_iden_alpha_beta --hidden_size 512 --app_encoder_size 512 --loss_beta 0.2 --loss_alpha 0.2

The codes contain four network model (DeepApp, DeepApp(App), DeepApp(App+Loc), DeepApp(App+User), RNN) and baseline model (MRU, MFU, HA, Bayes). The parameter settings for these model can refer to run.sh file.