pytorch implementation for CCA "Cascaded Cross Attention for Review-based Sequential Recommendation"
Create a folder named "datasets' and download the raw data from the Amamzon dataset into the subfloder
Run processed_data.py
Run CCA.py
Hello,
I am reviewing the GitHub code for the purpose of citing the CCA paper.
I noticed that in the CCA.py script, the following data is being loaded, but I cannot find the related data or code on GitHub
ItemFeatures = load_data('./datasets/%s/%s_review_emb_single.dat'%(fname,fname))
itemFeat = load_data('./datasets/%s/%s_review_emb_mean.dat'%(fname,fname))
The paper mentions that it uses 'bert-base-uncased' from Hugging Face,
and I am wondering if I could get the specific code related to this.
thank you
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