• UCGGAT
• Framework
• • Overview
  • Dependencies
  • Acknowledge

UCGGAT

UCGGAT: User Purchase Intention Prediction Based on User Fine-grained Module Click Stream of Product Detail Page

Framework

Overview

Here we provide the implementation of a User Click Graph-Graph Attention Network (UCGGAT) layer in TensorFlow. The repository is organised as follows:

• data/ put you data here (The data form is a diagram composed of click module flow);
• models/ contains the implementation of the UCGGAT network (ucggat.py);
• pre_trained/ contains a pre-trained UCGGAT model;

Finally, execute_ucg.py puts all of the above together and may be used to execute a full training run on you data by executing python execute_ucg.py.

Dependencies

The script has been tested running under Python 3.5.2, with the following packages installed (along with their dependencies):

• numpy==1.14.1
• scipy==1.0.0
• networkx==2.1
• tensorflow-gpu==1.6.0

In addition, CUDA 9.0 and cuDNN 7 have been used.

Acknowledge

This work was supported by the National Key R&D Program of China under Grant No. 2020AAA0103804 and partially supported by grants from the National Natural Science Foundation of China (No.72004021). This work belongs to the University of science and technology of China.