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---
task_categories:
- text-classification
language:
- vi
---
## VLSP2018-ABSA-Restaurant
### Dataset Summary
The VLSP 2018 Restaurant corpus targets the same ACSA sub-tasks (ACD & SPC) on **4,751** Vietnamese restaurant reviews. This unified CSV includes:
* **12** aspect–category indicator columns, each with values {0, 1, 2, 3}.
* A `type` column for train/dev/test.
* A `dataset` column fixed to `VLSP2018-ABSA-Restaurant`.
### Supported Tasks and Metrics
* **Aspect Category Detection**
* **Sentiment Polarity Classification**
* **Metrics:** Precision, Recall, F1
### Languages
* Vietnamese
### Dataset Structure
| Column | Type | Description |
| ----------------------------- | ----- | ----------------------------------------------------------------- |
| `Review` | `str` | The raw restaurant review. |
| `<Aspect#Category>` (12 cols) | `int` | Polarity indicator (0=absent, 1=positive, 2=negative, 3=neutral). |
| `type` | `str` | Split: `train` / `validation` / `test`. |
| `dataset` | `str` | Always `VLSP2018-ABSA-Restaurant`. |
The 12 aspect–category columns:
```
AMBIENCE#GENERAL, DRINKS#PRICES, …, SERVICE#GENERAL
```
### Usage
```python
from datasets import load_dataset
ds = load_dataset("visolex/vlsp2018-absa-restaurant")
train = ds.filter(lambda ex: ex["type"] == "train")
val = ds.filter(lambda ex: ex["type"] == "dev")
test = ds.filter(lambda ex: ex["type"] == "test")
print(train.features)
```
### Source & Links
* **GitHub:** [https://github.com/ds4v/absa-vlsp-2018](https://github.com/ds4v/absa-vlsp-2018 "https://github.com/ds4v/absa-vlsp-2018")
* **Publication:** End-to-end Multi-task Solutions for ACSA on Vietnamese (VLSP 2018) ([github.com][1])
---
### Citation
```bibtex
@INPROCEEDINGS{9865479,
author={Dang, Hoang-Quan and Nguyen, Duc-Duy-Anh and Do, Trong-Hop},
booktitle={2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom)},
title={Multi-task Solution for Aspect Category Sentiment Analysis on Vietnamese Datasets},
year={2022},
volume={},
number={},
pages={404-409},
keywords={Sentiment analysis;Analytical models;Computational modeling;Multitasking;Task analysis;Cybernetics;Computational intelligence;Aspect-based Sentiment Analysis;PhoBERT;Aspect Category Detection;Sentiment Polarity Classification},
doi={10.1109/CyberneticsCom55287.2022.9865479}}
}
```