• 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 (Sponsor: Hefu Liu) 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.