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Amazon_Luxury_Beauty_2018

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metadata
dataset_info:
  - config_name: metadata
    features:
      - name: asin
        dtype: string
      - name: title
        dtype: string
      - name: description
        dtype: string
      - name: brand
        dtype: string
      - name: main_cat
        dtype: string
      - name: category
        sequence: 'null'
      - name: also_buy
        sequence: string
      - name: also_view
        sequence: string
      - name: imageURL
        sequence: string
      - name: imageURLHighRes
        sequence: string
    splits:
      - name: train
        num_bytes: 24898313
        num_examples: 12299
    download_size: 9490355
    dataset_size: 24898313
  - config_name: reviews
    features:
      - name: reviewerID
        dtype: string
      - name: reviewerName
        dtype: string
      - name: overall
        sequence: int64
      - name: reviewTime
        sequence: timestamp[us]
      - name: asin
        sequence: string
      - name: reviewText
        sequence: string
      - name: summary
        sequence: string
    splits:
      - name: train
        num_bytes: 24663121
        num_examples: 6107
    download_size: 11955594
    dataset_size: 24663121
configs:
  - config_name: metadata
    data_files:
      - split: train
        path: metadata/train-*
  - config_name: reviews
    data_files:
      - split: train
        path: reviews/train-*

Amazon Luxury Beauty Dataset

Directory Structure

  • metadata: Contains product information.
  • reviews: Contains user reviews about the products.
  • filtered:
    • e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
    • metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
    • reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only perfect 5-star ratings with a minimum of 5 ratings.

Usage

Download metadata 

metadata = load_dataset(path="smartcat/Amazon_Luxury_Beauty_2018", name="metadata", split="train")

Download reviews 

metadata = load_dataset(path="smartcat/Amazon_Luxury_Beauty_2018", name="reviews", split="train")

Download filtered files 

filtered_reviews = load_dataset(
    path="smartcat/Amazon_Luxury_Beauty_2018",
    data_files="filtered/reviews.jsonl",
    split="train",
)

📎 Note: You can set any file or list of files from the "filtered" directory as the "data_files" argument.