README.md

metadata

dataset_info:
  features:
    - name: example_id
      dtype: int64
    - name: query
      dtype: string
    - name: query_id
      dtype: int64
    - name: product_id
      dtype: string
    - name: product_locale
      dtype: string
    - name: esci_label
      dtype: string
    - name: small_version
      dtype: int64
    - name: large_version
      dtype: int64
    - name: product_title
      dtype: string
    - name: product_description
      dtype: string
    - name: product_bullet_point
      dtype: string
    - name: product_brand
      dtype: string
    - name: product_color
      dtype: string
    - name: product_text
      dtype: string
  splits:
    - name: train
      num_bytes: 5047037946
      num_examples: 2027874
    - name: test
      num_bytes: 1631847321
      num_examples: 652490
  download_size: 2517788457
  dataset_size: 6678885267
license: apache-2.0
task_categories:
  - text-classification
  - text-retrieval
language:
  - en
  - ja
  - es

Dataset Card for "esci"

ESCI product search dataset https://github.com/amazon-science/esci-data/

Preprocessings:

-joined the two relevant files

-product_text aggregate all product text

-mapped esci_label to full name

@article{reddy2022shopping,
title={Shopping Queries Dataset: A Large-Scale {ESCI} Benchmark for Improving Product Search},
author={Chandan K. Reddy and Lluís Màrquez and Fran Valero and Nikhil Rao and Hugo Zaragoza and Sambaran Bandyopadhyay and Arnab Biswas and Anlu Xing and Karthik Subbian},
year={2022},
eprint={2206.06588},
archivePrefix={arXiv}
}