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---
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: 1722102154.0
num_examples: 3888
download_size: 1721187321
dataset_size: 1722102154.0
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](https://xmrec.github.io/data/fr/).
In particular, we have made the images available as PILs.
Possible use cases are :
- text classification, using the `categories` column as a label
- product recommendation using the `related` column
- hybrid text/image search (cf. [this Jina.ai blog post](https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/))
## 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}}
```
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