model card

README.md

@@ -0,0 +1,90 @@
+---
+annotations_creators:
+- no-annotation
+language:
+- zh
+language_creators:
+- found
+license:
+- apache-2.0
+pretty_name: CSL
+size_categories:
+- 1M<n<10M
+source_datasets:
+- extended|csl
+tags: []
+task_categories:
+- text-retrieval
+task_ids:
+- document-retrieval
+---
+
+# Dataset Card for CSL
+
+## Dataset Description
+
+CSL is the Chinese Scientific Literature Dataset.
+
+- **Paper:** https://aclanthology.org/2022.coling-1.344
+- **Repository:** https://github.com/ydli-ai/CSL
+
+### Dataset Summary
+
+The dataset contains titles, abstracts, keywords of papers written in Chinese from several academic fields.
+
+### Languages
+
+ - Chinese
+
+## Dataset Structure
+
+### Data Instances
+
+| Split           | Documents |
+|-----------------|----------:|
+| `csl`           |      396k |
+
+### Data Fields
+ - `id`: unique identifier for this document
+ - `cc_file`: source file from connon crawl
+ - `time`: extracted date/time from article
+ - `title`: title extracted from article
+ - `text`: extracted article body
+ - `url`: source URL
+
+## Dataset Usage
+
+Using 🤗 Datasets:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('neuclir/csl')['csl']
+```
+
+## License & Citation
+
+This dataset is based off the [Chinese Scientific Literature Dataset](https://github.com/ydli-ai/CSL) under Apache 2.0.
+The primay change is the addition of English translactions of the category and discipline descriptions by a native speaker.
+
+If you use this data, please cite:
+
+```
+@inproceedings{li-etal-2022-csl,
+    title = "{CSL}: A Large-scale {C}hinese Scientific Literature Dataset",
+    author = "Li, Yudong  and
+      Zhang, Yuqing  and
+      Zhao, Zhe  and
+      Shen, Linlin  and
+      Liu, Weijie  and
+      Mao, Weiquan  and
+      Zhang, Hui",
+    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
+    month = oct,
+    year = "2022",
+    address = "Gyeongju, Republic of Korea",
+    publisher = "International Committee on Computational Linguistics",
+    url = "https://aclanthology.org/2022.coling-1.344",
+    pages = "3917--3923",
+}
+```