liyinchao / AITM

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper submitted to KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition.

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AITM

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework.
Code for the paper accepted by KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. [https://arxiv.org/abs/2105.08489]

Requirement

python==3.6
tensorflow-gpu==1.10.0
keras==2.1.5

Dataset

We use the public Ali-CCP (Alibaba Click and Conversion Prediction) dataset. [https://tianchi.aliyun.com/datalab/dataSet.html?dataId=408].

Please download and unzip the dataset first.

Split the data to train/validation/test files to run the codes directly:

python process_public_dataset.py

Example to run the model

python AITM.py --embedded_dim 5 --lr 1e-3 --early_stop 1 --lamda 1e-6 --prefix AITM --weight 0.6

The instruction of commands has been clearly stated in the codes (see the parse_args function).

A Pytorch implementation

[https://github.com/adtalos/AITM-torch]

Last Update Date: Dec. 13, 2021 (UTC+8)

About

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper submitted to KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition.

License:MIT License


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