---
language:
  - vi
license: apache-2.0
pretty_name: UVB - Underthesea Vietnamese Books Dataset
tags:
  - vietnamese
  - books
  - fiction
  - literature
  - text-corpus
  - goodreads
  - nlp
task_categories:
  - text-generation
  - fill-mask
  - feature-extraction
size_categories:
  - 100<n<1K
annotations_creators:
  - machine-generated
language_creators:
  - found
source_datasets:
  - tmnam20/Vietnamese-Book-Corpus
  - BrightData/Goodreads-Books
dataset_info:
  features:
    - name: id
      dtype: string
    - name: title
      dtype: string
    - name: author
      dtype: string
    - name: content
      dtype: string
    - name: genres
      sequence: string
    - name: first_publish
      dtype: string
    - name: goodreads_id
      dtype: string
    - name: goodreads_url
      dtype: string
    - name: goodreads_rating
      dtype: float64
    - name: goodreads_num_ratings
      dtype: int64
  splits:
    - name: train
      num_examples: 447
  download_size: 219000000
  dataset_size: 219000000
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.jsonl
---

# UVB - Underthesea Vietnamese Books Dataset

A collection of 447 Vietnamese books with full text content and Goodreads metadata for NLP research.

## Dataset Description

- **Homepage:** [Underthesea NLP](https://github.com/undertheseanlp/underthesea)
- **Repository:** [HuggingFace](https://huggingface.co/datasets/undertheseanlp/UVB-v0.1)
- **Point of Contact:** [Underthesea NLP](https://github.com/undertheseanlp)

### Dataset Summary

UVB (Underthesea Vietnamese Books) is a dataset containing 447 Vietnamese books with full text content, mapped to Goodreads for metadata enrichment including genres, ratings, and publication years. The dataset is designed for Vietnamese language model training, text generation, and other NLP tasks.

### Supported Tasks

- **Language Modeling:** Pre-training or fine-tuning Vietnamese language models
- **Text Generation:** Training models to generate Vietnamese text
- **Text Classification:** Using genres as labels for classification tasks
- **Information Extraction:** Extracting structured information from book texts

### Languages

Vietnamese (vi)

## Dataset Structure

### Data Instances

```json
{
  "id": "vn_000001",
  "title": "The DIGITAL ECONOMY 20th Anniversary Edition",
  "author": "Don Tapscott",
  "content": "The DIGITAL ECONOMY 20th Anniversary Edition Rethinking Promise and Peril...",
  "genres": ["Business", "Paradigm Shift"],
  "first_publish": "2014",
  "goodreads_id": "20722002-the-digital-economy",
  "goodreads_url": "https://www.goodreads.com/book/show/20722002-the-digital-economy",
  "goodreads_rating": 4.1,
  "goodreads_num_ratings": 29
}
```

### Data Fields

| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Unique identifier (e.g., vn_000001) |
| `title` | string | Book title |
| `author` | string | Author name |
| `content` | string | Full text content of the book |
| `genres` | list[string] | Book genres from Goodreads |
| `first_publish` | string | First publication year |
| `goodreads_id` | string | Goodreads book ID |
| `goodreads_url` | string | Goodreads URL |
| `goodreads_rating` | float | Goodreads rating (1-5) |
| `goodreads_num_ratings` | int | Number of ratings on Goodreads |

### Data Splits

| Split | Examples |
|-------|----------|
| train | 447 |

### Dataset Statistics

- **Total books:** 447
- **Books with genres:** 230 (51.5%)
- **Books with publication year:** 421 (94.2%)
- **Total size:** ~209 MB

**Top Genres:**
| Genre | Count |
|-------|-------|
| Non Fiction | 76 |
| Fiction | 62 |
| Romance | 37 |
| Classics | 30 |
| Novels | 27 |
| Philosophy | 25 |
| Self Help | 25 |

**Publication Year Distribution:**
| Period | Count |
|--------|-------|
| Before 1900 | 6 |
| 1900-1950 | 12 |
| 1951-1980 | 38 |
| 1981-2000 | 82 |
| 2001-2010 | 134 |
| 2011+ | 149 |

## Dataset Creation

### Source Data

- **Vietnamese books:** [tmnam20/Vietnamese-Book-Corpus](https://huggingface.co/datasets/tmnam20/Vietnamese-Book-Corpus)
- **Goodreads metadata:** [BrightData/Goodreads-Books](https://huggingface.co/datasets/BrightData/Goodreads-Books)

### Data Collection

1. Vietnamese books were loaded from the source corpus
2. Books were matched to Goodreads entries using fuzzy title/author matching
3. Genres and publication years were scraped from Goodreads pages
4. Data was merged into a single dataset with full text content

### Processing Scripts

Processing scripts are included in the `scripts/` directory:
- `map_goodreads.py` - Map Vietnamese books to Goodreads entries
- `add_genres.py` - Fetch genres from Goodreads
- `add_publish_date.py` - Fetch first publication year
- `requirements.txt` - Python dependencies

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("undertheseanlp/UVB-v0.1")

# Access the data
for item in dataset["train"]:
    print(f"Title: {item['title']}")
    print(f"Author: {item['author']}")
    print(f"Content: {item['content'][:200]}...")
    print(f"Genres: {item['genres']}")
    print(f"First publish: {item['first_publish']}")
    break

# Filter by genre
fiction_books = [item for item in dataset["train"] if "Fiction" in (item.get("genres") or [])]
print(f"Found {len(fiction_books)} fiction books")
```

## Considerations for Using the Data

### Social Impact

This dataset can help advance Vietnamese NLP research and applications, contributing to language technology for Vietnamese speakers.

### Limitations

- Book content may contain OCR errors from digitization
- Genre and metadata coverage is not 100%
- Some author names may include translator information

## Additional Information

### Licensing

Apache 2.0

### Citation

```bibtex
@misc{uvb_dataset,
  title={UVB: Underthesea Vietnamese Books Dataset},
  author={Underthesea NLP},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/undertheseanlp/UVB-v0.1}
}
```

### Contributions

Thanks to [@rain1024](https://github.com/rain1024) for creating this dataset.