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