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@@ -12,4 +12,89 @@ tags:
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  - amazon
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  size_categories:
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  - 100K<n<1M
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - amazon
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  size_categories:
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  - 100K<n<1M
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+ ---
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+
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+ # Dataset Card for Amazon Products 2023
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+
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+ ## Dataset Summary
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+
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+ This dataset contains product metadata from Amazon, filtered to include only products that became available in 2023. The dataset is intended for use in semantic search applications and includes a variety of product categories.
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+
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+ - **Number of Rows:** 117,243
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+ - **Number of Columns:** 15
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+
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+ ## Data Source
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+
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+ The data is sourced from [Amazon Reviews 2023](https://amazon-reviews-2023.github.io/). It includes product information across multiple categories, with embeddings created using the `text-embedding-3-small` model.
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+
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+ ## Dataset Structure
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+
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+ ### Columns
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+
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+ - **parent_asin (str):** Unique identifier for the product.
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+ - **date_first_available (datetime64[ns]):** The date when the product first became available.
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+ - **title (str):** Title of the product.
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+ - **description (str):** Description of the product.
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+ - **filename (str):** Filename associated with the product metadata.
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+ - **main_category (str):** Main category of the product.
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+ - **categories (List[str]):** Subcategories of the product.
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+ - **store (str):** Store information for the product.
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+ - **average_rating (float64):** Average rating of the product.
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+ - **rating_number (float64):** Number of ratings for the product.
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+ - **price (float64):** Price of the product.
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+ - **features (List[str]):** Features of the product.
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+ - **details (str):** Additional details of the product. The string is JSON serializable.
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+ - **embeddings (List[float64]):** Embeddings generated for the product using `text-embedding-3-small` model.
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+ - **image (str):** URL of the product image.
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+
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+ ### Missing Values
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+
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+ - **main_category:** 24,805 missing values
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+ - **store:** 253 missing values
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+ - **rating_number:** 6 missing values
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+ - **price:** 35,869 missing values
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+
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+ ### Sample Data
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+
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+ ```json
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+ [
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+ {
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+ "parent_asin": "B000044U2O",
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+ "date_first_available": "2023-04-29T00:00:00",
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+ "title": "Anomie & Bonhomie",
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+ "description": "Amazon.com Fans of Scritti Politti's synth-pop-funk masterpiece Cupid & Psyche 85 may be shocked by how far afield Scritti mastermind Green Gartside has gone since then. Anomie & Bonhomie, his return to recording after a decadelong absence, ranges from guest shots by rappers and funksters such as Mos Def and Me'Shell Ndegeocello to Foo Fighters tributes. Gartside's trademark breathy vocals and spot-on melodicism do find their places here, but are often forced to make way for other influences. Neither a total success nor a total failure, Anomie does display a spark that makes one hope that Gartside doesn't wait so long to record again. --Rickey Wright",
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+ "filename": "meta_Digital_Music",
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+ "main_category": "Digital Music",
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+ "categories": [],
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+ "store": "Scritti Politti Format: Audio CD",
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+ "average_rating": 4.2,
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+ "rating_number": 56.0,
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+ "price": null,
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+ "features": [],
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+ "details": "{'Date First Available': 'April 29, 2023'}",
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+ "embeddings": [],
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+ "image": "https://m.media-amazon.com/images/I/41T618NE88L.jpg"
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+ },
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+ ...
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+ ]
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+ ```
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+
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+ ### Usage
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+ This dataset can be used for various applications, including:
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+
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+ - Semantic Search: Utilizing the embeddings to find similar products based on textual descriptions.
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+ - Product Recommendation: Enhancing recommendation systems with detailed product metadata.
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+
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+ ### Citation
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+
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+ ```bibtex
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+ @article{hou2024bridging,
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+ title={Bridging Language and Items for Retrieval and Recommendation},
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+ author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
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+ journal={arXiv preprint arXiv:2403.03952},
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+ year={2024}
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+ }
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+ ```
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+
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+ ### Contact
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+ For questions or issues regarding the dataset, please contact [Amazon Reviews 2023](https://amazon-reviews-2023.github.io/).