--- 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}} ```