Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Korean
Size:
100K - 1M
License:
Update README.md
Browse files
README.md
CHANGED
@@ -11,7 +11,6 @@ In other words, this dataset is basically a **binary** sentiment classficiation
|
|
11 |
|
12 |
### 🔍 See More
|
13 |
See all the codes for crwaling/preprocessing the dataset and experiments with KR3 in [Gitlab Repo](https://gitlab.com/Wittgensteinian/kr3).
|
14 |
-
Read our blog post in [DIYA Blog Post](.).
|
15 |
See Kaggle dataset in [Kaggle Dataset](https://www.kaggle.com/ninetyninenewton/kr3-korean-restaurant-reviews-with-ratings).
|
16 |
|
17 |
### Legal Issues
|
@@ -28,5 +27,5 @@ We concluded that the **non-commerical usage and release of KR3 fall into the ra
|
|
28 |
|
29 |
[Yejoon Lee](https://github.com/wittgensteinian)
|
30 |
|
31 |
-
This work was done as DIYA 4기. Compute resources needed for the work was supported by [DIYA](https://blog.diyaml.com) and
|
32 |
|
|
|
11 |
|
12 |
### 🔍 See More
|
13 |
See all the codes for crwaling/preprocessing the dataset and experiments with KR3 in [Gitlab Repo](https://gitlab.com/Wittgensteinian/kr3).
|
|
|
14 |
See Kaggle dataset in [Kaggle Dataset](https://www.kaggle.com/ninetyninenewton/kr3-korean-restaurant-reviews-with-ratings).
|
15 |
|
16 |
### Legal Issues
|
|
|
27 |
|
28 |
[Yejoon Lee](https://github.com/wittgensteinian)
|
29 |
|
30 |
+
This work was done as DIYA 4기. Compute resources needed for the work was supported by [DIYA](https://blog.diyaml.com) and surromind.ai.
|
31 |
|