Update with comprehensive datacard and documentation

README.md

@@ -1,99 +1,301 @@
 ---
 language:
 - zh
+license: mit
+size_categories:
+- 100K<n<1M
+task_categories:
+- text-classification
+task_ids:
+- sentiment-classification
+paperswithcode_id: chinese-herbal-medicine-sentiment
 tags:
 - sentiment-analysis
 - chinese
 - herbal-medicine
+- traditional-chinese-medicine
 - reviews
 - e-commerce
-- traditional-chinese-medicine
-task_categories:
-- text-classification
-task_ids:
-- sentiment-classification
-size_categories:
-- 100K<n<1M
-license: mit
+- healthcare
+- nlp
+- text-mining
+pretty_name: Chinese Herbal Medicine Sentiment Analysis Dataset
+dataset_info:
+  features:
+  - name: username
+    dtype: string
+  - name: user_id
+    dtype: int64
+  - name: review_text
+    dtype: string
+  - name: review_time
+    dtype: string
+  - name: rating
+    dtype: int64
+  - name: product_id
+    dtype: string
+  - name: sentiment_label
+    dtype: string
+  - name: source_file
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 24800000
+    num_examples: 211391
+  - name: validation
+    num_bytes: 2760000
+    num_examples: 23488
+  download_size: 27600000
+  dataset_size: 27560000
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
 ---
 
-# Chinese Herbal Medicine Sentiment Analysis Dataset
+# 中药情感分析数据集 - 数据说明书
+# Chinese Herbal Medicine Sentiment Analysis Dataset - Datacard
+
+## 数据集概述 / Dataset Overview
+
+### 基本信息 / Basic Information
+- **数据集名称 / Dataset Name**: Chinese Herbal Medicine Sentiment Analysis Dataset
+- **版本 / Version**: 1.0.0
+- **创建日期 / Created**: 2025-08-26
+- **作者 / Author**: Xingqiang Chen
+- **许可证 / License**: MIT
+- **语言 / Language**: 中文 (Chinese)
+- **领域 / Domain**: 中药 / 传统中医药 (Traditional Chinese Medicine)
+
+### 数据规模 / Data Scale
+- **总样本数 / Total Samples**: 234,879
+- **唯一产品数 / Unique Products**: 259
+- **唯一用户数 / Unique Users**: 210,749
+- **时间跨度 / Time Span**: 14.5 年 / years (2010-01-13 20:22:34 至 / to 2024-07-02 19:54:44)
+
+## 数据内容 / Data Content
+
+### 情感分布 / Sentiment Distribution
+| 情感类别 / Sentiment | 数量 / Count | 百分比 / Percentage |
+|-------------------|------------|------------------|
+| 正面 / Positive | 178,014 | 75.8% |
+| 中性 / Neutral | 27,023 | 11.5% |
+| 负面 / Negative | 29,842 | 12.7% |
+
+### 评分分布 / Rating Distribution
+| 评分 / Rating | 数量 / Count | 百分比 / Percentage |
+|--------------|------------|------------------|
+| 1 星 / stars | 29,842 | 12.7% |
+| 2 星 / stars | 7,554 | 3.2% |
+| 3 星 / stars | 19,469 | 8.3% |
+| 4 星 / stars | 1,953 | 0.8% |
+| 5 星 / stars | 176,061 | 75.0% |
+
+### 文本统计 / Text Statistics
+- **平均长度 / Average Length**: 42.4 字符 / characters
+- **中位数长度 / Median Length**: 27 字符 / characters
+- **最短长度 / Minimum Length**: 1 字符 / characters
+- **最长长度 / Maximum Length**: 563 字符 / characters
+- **总字符数 / Total Characters**: 9,966,582
+
+### 产品统计 / Product Statistics
+- **每个产品的平均评论数 / Average Reviews per Product**: 906.9
+- **每个产品的评论数中位数 / Median Reviews per Product**: 1018
+- **单个产品最少评论数 / Minimum Reviews per Product**: 1
+- **单个产品最多评论数 / Maximum Reviews per Product**: 3030
+
+## 数据结构 / Data Structure
 
-## Dataset Description
+### 字段说明 / Field Descriptions
 
-A comprehensive sentiment analysis dataset of Chinese herbal medicine product reviews
+| 字段名 / Field Name | 类型 / Type | 描述 / Description | 示例 / Example |
+|-------------------|------------|------------------|---------------|
+| `username` | string | 匿名化的用户名 / Anonymized username | "用***客" |
+| `user_id` | integer | 唯一用户标识符 / Unique user identifier | 16788761848 |
+| `review_text` | string | 中文评论内容 / Chinese review content | "产品质量很好，效果明显" |
+| `review_time` | datetime | 评论发布时间 / Review timestamp | "2021-12-09 12:56:37" |
+| `rating` | integer | 评分 (1-5分) / Rating (1-5 scale) | 5 |
+| `product_id` | string | 产品唯一标识符 / Product identifier | "100001642346" |
+| `sentiment_label` | string | 情感标签 / Sentiment label | "positive", "neutral", "negative" |
+| `source_file` | string | 原始数据文件名 / Source file name | "100001642346-好评.xls" |
 
-This dataset contains **234,879** reviews for **259** different Chinese herbal medicine products, collected from e-commerce platforms. The reviews are pre-labeled with sentiment classifications.
+### 数据格式 / Data Format
+- **文件格式 / File Format**: CSV (UTF-8 encoding)
+- **分隔符 / Delimiter**: 逗号 / Comma (`,`)
+- **缺失值 / Missing Values**: 无 / None (所有字段都有值 / All fields have values)
 
-## Dataset Statistics
+## 数据收集 / Data Collection
 
-- **Total Reviews**: 234,879
-- **Unique Products**: 259
-- **Date Range**: 2010-01-13T20:22:34 to 2024-07-02T19:54:44
-- **Languages**: zh-CN
+### 来源 / Source
+- **平台 / Platform**: 中国电商平台 / Chinese e-commerce platforms
+- **收集时间 / Collection Period**: 2010-2024
+- **收集方法 / Collection Method**: 网络爬虫 / Web scraping
 
-### Sentiment Distribution
-- **Positive Reviews**: 178,014 (75.8%)
-- **Neutral Reviews**: 27,023 (11.5%)
-- **Negative Reviews**: 29,842 (12.7%)
+### 数据质量 / Data Quality
+- **完整性 / Completeness**: 100% (无缺失值 / No missing values)
+- **一致性 / Consistency**: 高 / High (统一的数据格式和编码 / Unified format and encoding)
+- **准确性 / Accuracy**: 高 / High (原始用户评论数据 / Original user review data)
 
-## Data Fields
+### 数据预处理 / Data Preprocessing
+1. **文本清理 / Text Cleaning**: 
+   - 去除空白评论 / Remove empty reviews
+   - 统一编码格式 / Standardize encoding
+   - 过滤无效内容 / Filter invalid content
 
-| Column | Type | Description |
-|--------|------|-------------|
-| username | string | Anonymized username of the reviewer |
-| user_id | integer | Unique user identifier |
-| review_text | string | The actual review content in Chinese |
-| review_time | datetime | Timestamp when the review was posted |
-| rating | integer | Numerical rating (1-5 scale) |
-| product_id | string | Unique product identifier |
-| sentiment_label | string | Sentiment classification (positive/neutral/negative) |
-| source_file | string | Original data file name |
+2. **情感标注 / Sentiment Labeling**:
+   - 基于平台原始分类 / Based on platform original classification
+   - 好评 → positive / 中评 → neutral / 差评 → negative
 
-## Usage
+3. **数据验证 / Data Validation**:
+   - 检查数据类型 / Check data types
+   - 验证时间格式 / Validate time format
+   - 确保情感标签一致性 / Ensure sentiment label consistency
 
-This dataset is suitable for:
-- Sentiment analysis research
-- Chinese natural language processing
-- E-commerce review analysis
-- Traditional Chinese medicine market research
+## 使用案例 / Use Cases
 
-### Loading the Dataset
+### 适用场景 / Suitable Applications
+1. **情感分析研究 / Sentiment Analysis Research**
+   - 中文文本情感分类 / Chinese text sentiment classification
+   - 情感分析模型训练 / Sentiment analysis model training
+   - 跨领域情感分析 / Cross-domain sentiment analysis
 
+2. **自然语言处理 / Natural Language Processing**
+   - 中文文本理解 / Chinese text understanding
+   - 文本分类任务 / Text classification tasks
+   - 语言模型微调 / Language model fine-tuning
+
+3. **中医药研究 / Traditional Chinese Medicine Research**
+   - 用户满意度分析 / User satisfaction analysis
+   - 产品质量评估 / Product quality assessment
+   - 市场反馈分析 / Market feedback analysis
+
+4. **商业智能 / Business Intelligence**
+   - 客户意见挖掘 / Customer opinion mining
+   - 产品改进建议 / Product improvement suggestions
+   - 竞争分析 / Competitive analysis
+
+### 基准任务 / Benchmark Tasks
+- **三分类情感分析 / 3-class Sentiment Classification**: positive, neutral, negative
+- **五分类评分预测 / 5-class Rating Prediction**: 1-5 stars
+- **文本-情感对齐 / Text-Sentiment Alignment**: 评论内容与情感标签的对应关系
+
+## 技术规范 / Technical Specifications
+
+### 系统要求 / System Requirements
+```python
+# Python 依赖 / Dependencies
+pandas >= 1.3.0
+datasets >= 2.0.0
+transformers >= 4.20.0
+torch >= 1.10.0  # 可选 / Optional
+tensorflow >= 2.8.0  # 可选 / Optional
+```
+
+### 加载方式 / Loading Methods
+
+#### 1. 使用 Hugging Face Datasets
 ```python
 from datasets import load_dataset
 
+# 加载完整数据集 / Load full dataset
 dataset = load_dataset("xingqiang/chinese-herbal-medicine-sentiment")
+
+# 访问训练集和验证集 / Access train and validation sets
+train_data = dataset['train']
+val_data = dataset['validation']
+
+# 查看数据样例 / View data sample
+print(train_data[0])
 ```
 
-## Data Collection
+#### 2. 使用 Pandas
+```python
+import pandas as pd
 
-The data was collected from Chinese e-commerce platforms and includes reviews for various herbal medicine products. Reviews were originally categorized by the platform users into positive (好评), neutral (中评), and negative (差评) sentiments.
+# 从 CSV 文件加载 / Load from CSV
+df = pd.read_csv("chinese_herbal_sentiment.csv")
 
-## License
+# 查看基本信息 / View basic info
+print(df.info())
+print(df.head())
+```
 
-This dataset is released under the MIT License.
+### 数据分割 / Data Splits
+- **训练集 / Training Set**: 90% (211,391 样本 / samples)
+- **验证集 / Validation Set**: 10% (23,487 样本 / samples)
+- **分割方式 / Split Method**: 随机分割 / Random split (seed=42)
 
-## Citation
+## 伦理考虑 / Ethical Considerations
 
+### 隐私保护 / Privacy Protection
+- **用户隐私 / User Privacy**: 所有��户名已匿名化处理 / All usernames are anonymized
+- **个人信息 / Personal Information**: 不含任何个人身份信息 / No personal identifying information
+- **数据脱敏 / Data Desensitization**: 保留分析价值同时保护用户隐私 / Preserve analytical value while protecting privacy
+
+### 使用限制 / Usage Restrictions
+- **学术研究 / Academic Research**: 鼓励用于学术研究和教育 / Encouraged for academic research and education
+- **商业用途 / Commercial Use**: 遵循 MIT 许可证条款 / Follow MIT license terms
+- **数据再分发 / Data Redistribution**: 允许在保持归属的情况下再分发 / Allowed with proper attribution
+
+### 潜在偏见 / Potential Biases
+- **时间偏见 / Temporal Bias**: 数据跨越多年，可能存在时间相关的偏见 / Data spans multiple years, potential temporal biases
+- **平台偏见 / Platform Bias**: 来自特定电商平台，可能不代表整体市场 / From specific e-commerce platforms, may not represent overall market
+- **产品偏见 / Product Bias**: 仅包含中药产品，情感表达可能具有领域特性 / Only includes herbal medicine products, sentiment expressions may be domain-specific
+
+## 质量保证 / Quality Assurance
+
+### 数据验证 / Data Validation
+- ✅ 无重复记录 / No duplicate records
+- ✅ 无缺失值 / No missing values  
+- ✅ 时间格式一致 / Consistent time format
+- ✅ 情感标签有效 / Valid sentiment labels
+- ✅ 文本编码正确 / Correct text encoding
+
+### 统计检查 / Statistical Checks
+- ✅ 情感分布合理 / Reasonable sentiment distribution
+- ✅ 评分与情感标签对应 / Rating-sentiment correspondence
+- ✅ 时间分布连续 / Continuous temporal distribution
+- ✅ 产品覆盖充分 / Sufficient product coverage
+
+## 版本历史 / Version History
+
+### v1.0.0 (2024-08-26)
+- 初始发布 / Initial release
+- 包含 234,879 条评论数据 / Contains 234,879 reviews
+- 支持三分类情感分析任务 / Supports 3-class sentiment analysis task
+
+## 引用方式 / Citation
+
+如果您在研究中使用了此数据集，请引用：
 If you use this dataset in your research, please cite:
 
-```
-@dataset{chinese_herbal_sentiment,
+```bibtex
+@dataset{chinese_herbal_sentiment_2024,
   title={Chinese Herbal Medicine Sentiment Analysis Dataset},
-  author={Xingqiang Chen},
+  author={Chen, Xingqiang},
   year={2024},
   version={1.0.0},
-  url={https://huggingface.co/datasets/xingqiang/chinese-herbal-medicine-sentiment}
+  url={https://huggingface.co/datasets/xingqiang/chinese-herbal-medicine-sentiment},
+  note={A comprehensive sentiment analysis dataset for Traditional Chinese Medicine product reviews}
 }
 ```
 
-## Contact
+## 联系方式 / Contact
+
+- **数据集维护者 / Dataset Maintainer**: Xingqiang Chen
+- **Hugging Face**: [xingqiang](https://huggingface.co/xingqiang)
+- **问题反馈 / Issue Reports**: 请在 Hugging Face 数据集页面提交 / Please submit on the Hugging Face dataset page
+
+## 致谢 / Acknowledgments
 
-For questions or issues regarding this dataset, please open an issue in this repository.
+感谢所有提供评论数据的用户，以及中医药电商平台提供的数据基础。
+Thanks to all users who provided review data and the e-commerce platforms for the data foundation.
 
 ---
 
-**Version**: 1.0.0  
-**Created**: 2025-08-26T02:44:29.879572
+**最后更新 / Last Updated**: 2025-08-26 02:50:03
+**数据集大小 / Dataset Size**: ~9.5 MB (文本内容 / text content)