ChenglongMa
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- reviews
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pretty_name: Amazon Reviews 2023 All-Category k-Core
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- 100M<n<1B
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---
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# Dataset Card for
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### Dataset Description
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<!-- Provide a longer summary of what this dataset is. -->
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- **Curated by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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### Dataset Sources [optional]
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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### Direct Use
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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[More Information Needed]
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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<!-- Motivation for the creation of this dataset. -->
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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[More Information Needed]
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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[More Information Needed]
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### Annotations [optional]
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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#### Annotation process
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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## Glossary [optional]
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Dataset Card Authors
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## Dataset Card Contact
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language:
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- en
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tags:
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- recommendation
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- reviews
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- ecommerce
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- ratings
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- user-behavior
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pretty_name: Amazon Reviews 2023 All-Category k-Core
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size_categories:
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- 100M<n<1B
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---
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# Dataset Card for `Amazon Reviews 2023 All-Category k-Core`
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* These datasets are subsets of [Amazon reviews dataset](https://amazon-reviews-2023.github.io/), collected in 2023 by [McAuley Lab](https://cseweb.ucsd.edu/~jmcauley/).
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* It contains **all categories** of the reviews from the original dataset that have more than $k \in [5, 20]$ interactions.
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* The original dataset contains reviews in the period of May. 1996 to Sep. 2023.
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* The reviews are grouped into 25 categories.
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* The dataset is in `.parquet` format.
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## Dataset Details
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### Dataset Description
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The dataset contains reviews from Amazon, and it is a subset of the original dataset. The dataset is in `.parquet` format.
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Please refer to the [Dataset Creation and Processing](#dataset-creation-and-processing) section for more details about the dataset.
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### Dataset Structure
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The repository is structured as follows:
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```
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amazon-2023-all-category-k-core/
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|- 5-core/
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|- 5-core.parquet # 5-core ratings of all categories, 3.16GB
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|- 20-core/
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|- category/
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|- Arts_Crafts_and_Sewing/
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|- ratings.parquet # ratings of Arts, Crafts & Sewing
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|- meta.parquet # meta data of items in Arts, Crafts & Sewing
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|- reviews.parquet # reviews of items in Arts, Crafts & Sewing
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|- ... # other categories
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|- 20-core.parquet # 20-core ratings of all categories, 1.1GB
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|- item_map.jsonl.gz # item map, format: [{item_index:int, parent_asin:str}], 7.97MB
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|- user_map.jsonl.gz # user map, format: [{user_index:int, user_id:str}], 29.4MB
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```
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## Dataset Creation and Processing
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1. Merge the `ratings` from all categories of [Amazon reviews 2023 dataset](https://amazon-reviews-2023.github.io/)
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2. Filter out the `ratings` that have less than $k$ interactions, where $k \in [5, 20]$.
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3. Filter out the `meta` data and `reviews` of items that are not in the filtered `ratings`.
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4. Save the datasets in `.parquet` format.
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## Dataset Sources
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The original dataset is available at [Amazon reviews dataset](https://amazon-reviews-2023.github.io/).
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<!-- - **Repository:** [More Information Needed] -->
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<!-- - **Paper [optional]:** [More Information Needed] -->
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<!-- - **Demo [optional]:** [More Information Needed] -->
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## Uses
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This dataset can be used for recommendation systems, sentiment analysis, and other NLP tasks.
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<!-- ## Citation [optional] -->
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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<!-- **BibTeX:** -->
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<!-- [More Information Needed] -->
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<!-- **APA:** -->
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<!-- [More Information Needed] -->
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## Glossary [optional]
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The glossary of the dataset is available at [Amazon Reviews#Data Fields](https://amazon-reviews-2023.github.io/#data-fields).
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## Dataset Card Authors
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Chenglong Ma
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## Dataset Card Contact
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https://huggingface.co/ChenglongMa
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