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MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems, RecSys 2020

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MultiRec

This is our implementation for the recsys 2020 paper:

Rashed, Ahmed, et al. "MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems."14th ACM Conference on Recommender Systems (RecSys). 2020.

Enviroment

* pandas==1.0.3
* tensorflow==1.14.0
* matplotlib==3.1.3
* numpy==1.18.1
* six==1.14.0
* scikit_learn==0.23.1

Steps

  1. Download the eBay dataset ("https://www.kaggle.com/onlineauctions/online-auctions-dataset/data#auction.csv")
  2. Place the auction.csv file under Data/ebay/
  3. Run the data preprocessing file "python DataPrep.py"
  4. To reproduce the paper results please run the following command "python MultiRec.py 5 1 1 0"

Paper

Preprint version : https://www.ismll.uni-hildesheim.de/pub/pdfs/Ahmed_RecSys20.pdf

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MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems, RecSys 2020

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