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A pytorch implementation of Criterion-based heterogeneous collaborative filtering for multi-behavior implicit recommendation

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README.md
README.md
 
 
beibei
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model_full.py
model_full.py
 
 
run_full.py
run_full.py
 
 
search.py
search.py
 
 
utils.py
utils.py
 
 

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A pytorch implementation for paper "Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation" [TKDD 2023]

REQUIREMENTS

  1. pytorch 1.4
  2. loguru
  3. scipy
  4. sklearn

DATASETS

[BeiBei][https://github.com/chenchongthu/EHCF] [Taobao][https://github.com/chenchongthu/EHCF]

EXPERIMENTS

Here we use the GMF as the CF basic model.

How to train Beibei : python search.py 0 [GPU_ID]

How to train Taobao : python search.py 1 [GPU_ID]

Our model will be restored in the checkpoints.

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A pytorch implementation of Criterion-based heterogeneous collaborative filtering for multi-behavior implicit recommendation

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