ChenglongMa/amazon-2023-all-category-k-core

Dataset Card for Amazon Reviews 2023 All-Category k-Core

• These datasets are subsets of Amazon reviews dataset, collected in 2023 by McAuley Lab.

• It contains all categories of the reviews from the original dataset that have more than $k \in [5, 20]$ interactions.

• The original dataset contains reviews in the period of May. 1996 to Sep. 2023.

• The reviews are grouped into 25 categories.

• The dataset is in .parquet format.

k-core means that every user and every item has at least k interactions across ALL categories combined.

This condition may not hold within a single category.

Dataset Details

Dataset Description

The dataset contains reviews from Amazon, and it is a subset of the original dataset. The dataset is in .parquet format.

Please refer to the Dataset Creation and Processing section for more details about the dataset.

Dataset Structure

The repository is structured as follows:

amazon-2023-all-category-k-core/
  |- 5-core/
     |- 5-core.parquet                 # 5-core ratings of all categories, 3.16GB
  |- 20-core/
     |- category/
        |- Arts_Crafts_and_Sewing/
           |- ratings.parquet          # ratings of Arts, Crafts & Sewing
           |- meta.parquet             # meta data of items in Arts, Crafts & Sewing
           |- reviews.parquet          # reviews of items in Arts, Crafts & Sewing
        |- ...                         # other categories
     |- 20-core.parquet                # 20-core ratings of all categories, 1.1GB
     |- item_map.jsonl.gz              # item map, format: [{item_index:int, parent_asin:str}], 7.97MB
     |- user_map.jsonl.gz              # user map, format: [{user_index:int, user_id:str}],     29.4MB

Dataset Creation and Processing

1. Merge the ratings from all categories of Amazon reviews 2023 dataset
2. Filter out the ratings that have less than $k$ interactions, where $k \in [5, 20]$.
3. Filter out the meta data and reviews of items that are not in the filtered ratings.
4. Save the datasets in .parquet format.

Dataset Sources

The original dataset is available at Amazon reviews dataset.

Uses

This dataset can be used for recommendation systems, sentiment analysis, and other NLP tasks.

Glossary

The glossary of the dataset is available at Amazon Reviews#Data Fields.

Dataset Card Authors

Chenglong Ma

Dataset Card Contact

https://huggingface.co/ChenglongMa