metadata
dataset_info:
features:
- name: asin
dtype: string
- name: title
dtype: string
- name: image
dtype: image
- name: categories
sequence: string
- name: description
dtype: string
- name: features
sequence: string
- name: overviewFeatures
struct:
- name: Dimensions de l'article L x L x H
dtype: string
- name: Marque
dtype: string
- name: Poids de l'article
dtype: string
- name: averageRating
dtype: string
- name: ratingCount
dtype: string
- name: ratingDist
struct:
- name: '1'
dtype: string
- name: '2'
dtype: string
- name: '3'
dtype: string
- name: '4'
dtype: string
- name: '5'
dtype: string
- name: price
dtype: string
- name: related
struct:
- name: alsoBought
sequence: string
- name: alsoViewed
sequence: string
- name: boughtTogether
sequence: string
- name: compared
sequence: 'null'
- name: sponsored
sequence: string
- name: productDetails
struct:
- name: dummy
dtype: 'null'
- name: sellerPage
dtype: string
- name: amazon_badge
dtype: string
splits:
- name: train
num_bytes: 1722102154
num_examples: 3888
download_size: 1721187321
dataset_size: 1722102154
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-classification
- text-retrieval
language:
- fra
Description
Cleaned version of the Movies and TV subset (metadata folder) of XMRec dataset.
In particular, we have made the images available as PILs.
Possible use cases are :
- text classification, using the
categoriescolumn as a label - product recommendation using the
relatedcolumn - hybrid text/image search (cf. this Jina.ai blog post)
Original paper citation
@inproceedings{bonab2021crossmarket,
author = {Bonab, Hamed and Aliannejadi, Mohammad and Vardasbi, Ali and Kanoulas, Evangelos and Allan, James},
booktitle = {Proceedings of the 30th ACM International Conference on Information \& Knowledge Management},
publisher = {ACM},
title = {Cross-Market Product Recommendation},
year = {2021}}