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smartcat/Amazon_Sports_and_Outdoors_2018

Amazon Sports & Outdoors Dataset Directory Structure metadata: Contains product information. reviews: Contains user reviews about the products. filtered: e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2. metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category. reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include… See the full description on the dataset page: https://huggingface.co/datasets/smartcat/Amazon_Sports_and_Outdoors_2018.

sourceHugging Faceupdated 2y agoView on Hugging Face
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Dataset Card

Amazon Sports & Outdoors Dataset

Directory Structure

  • —metadata: Contains product information.
  • —reviews: Contains user reviews about the products.
  • —filtered:
  • —e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
  • —metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
  • —reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only perfect 5-star ratings with a minimum of 5 ratings.

Usage

Download metadata

python
metadata = load_dataset(path="smartcat/Amazon_Sports_and_Outdoors_2018", name="metadata", split="train")

Download reviews

python
metadata = load_dataset(path="smartcat/Amazon_Sports_and_Outdoors_2018", name="reviews", split="train")

Download filtered files

filtered_reviews = load_dataset(
    path="smartcat/Amazon_Sports_and_Outdoors_2018",
    data_files="filtered/reviews.jsonl",
    split="train",
)

📎 Note: You can set any file or list of files from the "filtered" directory as the "data_files" argument.

Citation

Amazon Reviews 2023

bibtex
@article{hou2024bridging,
  title={Bridging language and items for retrieval and recommendation},
  author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
  journal={arXiv preprint arXiv:2403.03952},
  year={2024}
}

Amazon Reviews 2018

bibtex
@inproceedings{ni2019justifying,
  title={Justifying recommendations using distantly-labeled reviews and fine-grained aspects},
  author={Ni, Jianmo and Li, Jiacheng and McAuley, Julian},
  booktitle={Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)},
  pages={188--197},
  year={2019}
}

Amazon Reviews 2014

bibtex
@inproceedings{he2016ups,
  title={Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering},
  author={He, Ruining and McAuley, Julian},
  booktitle={proceedings of the 25th international conference on world wide web},
  pages={507--517},
  year={2016}
}
bibtex
@inproceedings{mcauley2015image,
  title={Image-based recommendations on styles and substitutes},
  author={McAuley, Julian and Targett, Christopher and Shi, Qinfeng and Van Den Hengel, Anton},
  booktitle={Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval},
  pages={43--52},
  year={2015}
}