body-check-test

本数据集来源自公开数据采样：https://www.heywhale.com/home/competition/609cc718ca31cd0017835fdc/content/1

该数据集包含从2011年1月1日到2014年3月31日（3年多）某电商网站的消费者购买行为，用户评分，评论和产品元数据，涵盖15个一级产品类别，987个二级产品类别，近2个百万用户，超过10万种产品和超过6,000万条评论。该数据集中的每个文本评论都包含三个子评论：正面评论，负面评论和整体评论。

- 本数据集包括52 万件商品，1100 多个类目，142 万用户，720 万条评论/评分数据
- 基于公开电商数据，针对部分字段做出了一定的调整
- 字段信息内容参考如下：

1 . 商品信息.csv

| 字段 | 数据 | 说明 |
| :------- | :----- | :----------------------------------------------------------- |
| 商品ID | string | 产品 id (PRODUCT_0) |
| 商品名称 | string | 商品的具体名称，例如“新编家常菜谱(名厨指导版)” |
| 所属类别 | string | 商品所属类别（从 0 开始，连续编号，从左到右依次表示一级类目、二级类目、三级类目） |

2 . 商品类别列表.csv

| 字段 | 数据 | 说明 |
| :------- | :----- | :---------------------------- |
| 类别ID | string | 类别 id (从 0 开始，连续编号) |
| 类别名称 | string | 类别名称 |

3 . 训练集

| 字段 | 数据 | 说明 |
| :--------- | :----- | :----------------------------- |
| 数据ID | string | 每条数据的唯一id，例如TRAIN_0 |
| 用户ID | int | 用户 id (从 0 开始，连续编号) |
| 商品ID | string | 即 products.csv 中的 productId |
| 评论时间戳 | int | 评分的时间戳 |
| 评论标题 | string | 评论的标题 |
| 评论内容 | string | 评论的内容 |
| 评分 | int | 评分，[1,5] 之间的整数 |

4 .测试集

| 字段 | 说明 |
| :--------- | :----------------------------- |
| 数据ID | 每条数据的唯一id，例如TRAIN_0 |
| 用户ID | 用户 id (从 0 开始，连续编号) |
| 商品ID | 即 products.csv 中的 productId |
| 评论时间戳 | 评分的时间戳 |
| 评论标题 | 评论的标题 |
| 评论内容 | 评论的内容 |

This dataset is sampled from public data: https://www.heywhale.com/home/competition/609cc718ca31cd0017835fdc/content/1

This dataset contains consumer purchase behavior, user ratings, reviews, and product metadata from an e-commerce website spanning from January 1, 2011 to March 31, 2014 (over 3 years). It covers 15 primary product categories, 987 secondary product categories, nearly 2 million users, more than 100,000 products, and over 60 million reviews. Each text review in this dataset includes three sub-reviews: positive review, negative review, and overall review.

Note: This dataset includes 520,000 products, over 1,100 categories, 1.42 million users, and 7.2 million review/rating data entries. It is adapted from public e-commerce data with adjustments made to some fields.

The field information is referenced as follows:

1. products_info.csv
| Field | Data Type | Description |
| :---------- | :-------- | :------------------------------------------------------------------ |
| Product ID | string | Product ID (format: PRODUCT_0) |
| Product Name| string | Specific name of the product, e.g., "Newly Compiled Home-Cooking Recipes (Chef's Guide Edition)" |
| Category Affiliation | string | Product category (numbered consecutively starting from 0; from left to right: primary category, secondary category, tertiary category) |

2. product_category_list.csv
| Field | Data Type | Description |
| :---------- | :-------- | :------------------------------------------------------------------ |
| Category ID | string | Category ID (numbered consecutively starting from 0) |
| Category Name| string | Category name |

3. Training Set
| Field | Data Type | Description |
| :---------- | :-------- | :------------------------------------------------------------------ |
| Data ID | string | Unique ID for each entry, e.g., TRAIN_0 |
| User ID | int | User ID (numbered consecutively starting from 0) |
| Product ID | string | Corresponding product ID in products_info.csv |
| Review Timestamp | int | Timestamp of the rating/review |
| Review Title| string | Title of the review |
| Review Content | string | Content of the review |
| Rating | int | Rating, an integer between 1 and 5 inclusive |

4. Test Set
| Field | Description |
| :---------- | :------------------------------------------------------------------ |
| Data ID | Unique ID for each entry, e.g., TRAIN_0 |
| User ID | User ID (numbered consecutively starting from 0) |
| Product ID | Corresponding product ID in products_info.csv |
| Review Timestamp | int | Timestamp of the rating/review |
| Review Title| string | Title of the review |
| Review Content | string | Content of the review |