Update README.md

README.md

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+
+## Openrice Sentiment Classification dataset
+
+From [github.com/Christainx/Dataset_Cantonese_Openrice](https://github.com/Christainx/Dataset_Cantonese_Openrice).
+
+The dataset includes 60k instances from Cantonese reviews in Openrice.
+
+The rating ranks from 1-star (very negative) to 5-star (very positive). The instances are shuffled in order to disperse reviews of same restaurant.
+
+### Code for the splits creation
+
+```
+import datasets
+
+def load_openrice():
+    # https://github.com/Christainx/Dataset_Cantonese_Openrice/blob/master/Openrice_Cantonese.7z
+    with open('Openrice_Cantonese.txt') as file:
+        for i, line in enumerate(file):
+            label = int(line[0])
+            text = line[1:].strip()
+            yield {'text': text, 'label': label}
+
+
+ds = datasets.Dataset.from_generator(load_openrice)
+print(ds)
+dsd = ds.train_test_split(0.2, seed=42)
+dsd['test'].to_json('data/test.jsonl', orient='records', force_ascii=False)
+dsd['train'].to_json('data/train.jsonl', orient='records', force_ascii=False)
+print(dsd)
+```
+
+## Citation
+```
+@inproceedings{xiang2019sentiment,
+  title={Sentiment Augmented Attention Network for Cantonese Restaurant Review Analysis},
+  author={Xiang, Rong and Jiao, Ying and Lu, Qin},
+  booktitle={Proceedings of the 8th KDD Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM)},
+  pages={1--9},
+  year={2019},
+  organization={KDD WISDOM}
+}
+```