/TAA_MindSpore

MindSpore implementation of Task-Adversarial Adaptation for Multi-modal Recommendation in ACM MM23

Primary LanguagePython

Task-Adversarial-Adaptation-for-Multi-modal-Recommendation

A MindSpore implementation

Overview

This library contains a MindSpore implementation of 'Task-Adversarial-Adaptation-for-Multi-modal-Recommendation'

Datasets

  • AliExpressDataset: This is a dataset gathered from real-world traffic logs of the search system in AliExpress. This dataset is collected from 5 countries: Russia, Spain, French, Netherlands, and America, which can utilized as 5 multi-task datasets. Original_dataset Processed_dataset Google Drive Processed_dataset Baidu Netdisk

    You can put the downloaded '.zip' files in ./data/ and run python preprocess.py --dataset_name NL to process the dataset.

Requirements

  • Python>=3.7
  • Mindspore==2.1.1
  • pandas
  • numpy
  • tqdm

Run

You can run a model through:

python main.py --model_name aitm --tgt_dataset_name AliExpress_US