Sequential recommendation datasets

Citation Author(s):
xj
s
Submitted by:
fuzhen sun
Last updated:
Thu, 10/10/2024 - 19:55
DOI:
10.21227/8w06-e721
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Abstract 

This dataset is a sequential recommendation dataset that includes three sub-datasets: Beauty, Toys, and Yelp, specifically designed for research and development in recommendation systems. All datasets have been pre-processed, allowing users to directly input them into the main program for use. These datasets are ready for experiments involving user-item interactions and can be used to train and evaluate recommendation algorithms. The command to run the datasets is: . The Beauty, Toys, and Yelp datasets reflect user interactions and ratings with a variety of products, making them suitable for diverse recommendation tasks.python main.py --data_name [dataset_name]

Instructions: 

This dataset is a sequential recommendation dataset that includes three sub-datasets: Beauty, Toys, and Yelp. Each dataset consists of pre-processed user interaction sequences, and they can be run using the command: python main.py --data_name [dataset_name]. The Beauty, Toys, and Yelp datasets contain user interaction ratings for different products. 

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Submitted by CHANG LU-CING on Mon, 10/21/2024 - 02:54

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