Update README.md

README.md

@@ -1,70 +1,91 @@
----
-dataset_info:
-  features:
-    - name: id
-      dtype: string
-    - name: text
-      dtype: string
-    - name: label
-      dtype: int64
-  splits:
-    - name: train
-      num_bytes: 652315
-      num_examples: 2624
-    - name: test
-      num_bytes: 66198
-      num_examples: 292
-  dataset_size: 718513
-configs:
-  - config_name: default
-    data_files:
-      - split: train
-        path: train-*.parquet
-      - split: test
-        path: test-*.parquet
----
-
-# Classical Chinese Poetry Theme Classification
-
-This dataset contains classical Chinese poetry with theme classification. Each poem is classified into one of 7 thematic categories.
-
-## Dataset Information
-
-The dataset is split into train and test sets.
-
-- **Train set**: 2624 examples
-- **Test set**: 292 examples
-- **Total**: 2916 examples
-
-## Data Format
-
-The dataset is stored in Parquet format with the following fields:
-
-- `id`: Unique identifier
-- `text`: Poem text
-- `label`: Theme label (integer from 1 to 7)
-
-## Theme Labels
-
-| Class | Thematic Category | Description | Number (Proportion) |
-|-------|-------------------|-------------|---------------------|
-| 1 | 爱情婚姻 (Love and Marriage) | This type of poetry typically expresses the joys, sorrows, and ups and downs of love, marriage, and family life. | 312 (10.7%) |
-| 2 | 交友送别 (Friendship and Farewell) | The works usually contain praise for friendship, sorrow for separation, and anticipation for a reunion. | 695 (23.8%) |
-| 3 | 羁旅思乡 (Journey and Homesickness) | This type of poetry expresses longing and attachment to one's hometown, homeland, and family, as well as the loneliness and helplessness of wandering and leaving one's hometown. | 353 (12.1%) |
-| 4 | 边塞战争 (Frontier and War) | This type of poetry reflects the loyalty, strength, courage, and sacrifice of soldiers in border wars. | 230 (7.9%) |
-| 5 | 山水田园 (Landscape and Countryside) | This type of poetry shows a love and longing for natural scenery, usually with beautiful imagery and rich emotional colors. | 368 (12.6%) |
-| 6 | 咏史怀古 (Historical allusions and Nostalgia) | This type of poetry expresses admiration for history, love for traditional culture, and contemplation of the changes in the times through the depiction and expression of historical events, famous figures, and cultural relics. | 387 (13.3%) |
-| 7 | 托物言志 (Expressing emotions through concrete objects) | This type of poetry expresses thoughts and emotions related to society, life, morality, and other aspects through the portrayal and symbolism of objects. | 573 (19.6%) |
-
-
-## Usage
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("PoetryMTEB/ClassicalChinesePoetryThemeClassification")
-
-# Access train and test splits
-train_data = dataset['train']
-test_data = dataset['test']
-```
+---
+dataset_info:
+  features:
+    - name: id
+      dtype: string
+    - name: text
+      dtype: string
+    - name: label
+      dtype: int64
+  splits:
+    - name: train
+      num_bytes: 652315
+      num_examples: 2624
+    - name: test
+      num_bytes: 66198
+      num_examples: 292
+  dataset_size: 718513
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: train-*.parquet
+      - split: test
+        path: test-*.parquet
+---
+
+# Classical Chinese Poetry Theme Classification
+
+This dataset contains classical Chinese poetry with theme classification. Each poem is classified into one of 7 thematic categories.
+
+## Dataset Information
+
+The dataset is split into train and test sets.
+
+- **Train set**: 2624 examples
+- **Test set**: 292 examples
+- **Total**: 2916 examples
+
+## Data Format
+
+The dataset is stored in Parquet format with the following fields:
+
+- `id`: Unique identifier
+- `text`: Poem text
+- `label`: Theme label (integer from 1 to 7)
+
+## Theme Labels
+
+| Class | Thematic Category | Description | Number (Proportion) |
+|-------|-------------------|-------------|---------------------|
+| 1 | 爱情婚姻 (Love and Marriage) | This type of poetry typically expresses the joys, sorrows, and ups and downs of love, marriage, and family life. | 312 (10.7%) |
+| 2 | 交友送别 (Friendship and Farewell) | The works usually contain praise for friendship, sorrow for separation, and anticipation for a reunion. | 695 (23.8%) |
+| 3 | 羁旅思乡 (Journey and Homesickness) | This type of poetry expresses longing and attachment to one's hometown, homeland, and family, as well as the loneliness and helplessness of wandering and leaving one's hometown. | 353 (12.1%) |
+| 4 | 边塞战争 (Frontier and War) | This type of poetry reflects the loyalty, strength, courage, and sacrifice of soldiers in border wars. | 230 (7.9%) |
+| 5 | 山水田园 (Landscape and Countryside) | This type of poetry shows a love and longing for natural scenery, usually with beautiful imagery and rich emotional colors. | 368 (12.6%) |
+| 6 | 咏史怀古 (Historical allusions and Nostalgia) | This type of poetry expresses admiration for history, love for traditional culture, and contemplation of the changes in the times through the depiction and expression of historical events, famous figures, and cultural relics. | 387 (13.3%) |
+| 7 | 托物言志 (Expressing emotions through concrete objects) | This type of poetry expresses thoughts and emotions related to society, life, morality, and other aspects through the portrayal and symbolism of objects. | 573 (19.6%) |
+
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("PoetryMTEB/ClassicalChinesePoetryThemeClassification")
+
+# Access train and test splits
+train_data = dataset['train']
+test_data = dataset['test']
+```
+```
+@article{10.1145/3685679,
+    author = {Hou, Jingrui and Zhang, Shitou},
+    title = {Exploring Thematic Diversity in Classical Chinese Poetry: A Novel Dataset and a BERT-enhanced Ensemble Learning Approach},
+    year = {2024},
+    issue_date = {December 2024},
+    publisher = {Association for Computing Machinery},
+    address = {New York, NY, USA},
+    volume = {17},
+    number = {4},
+    issn = {1556-4673},
+    url = {https://doi.org/10.1145/3685679},
+    doi = {10.1145/3685679},
+    abstract = {Classical Chinese poetry, as an essential aspect of cultural heritage, exhibits rich theme diversity often overlooked in natural language processing research. To address this gap, we aim to explore the classification of thematic categories within this literary domain. We curate a dataset of 2,918 annotated poems spanning 7 common themes and propose a BERT-based ensemble learning approach for effective classification. Although this method integrates existing models, it achieves an accuracy and F1 score of over 72\% in the 7-class task, surpassing established baselines, and providing a baseline for future research. The experimental findings reveal the effectiveness of ensemble strategies in improving individual base model performance and highlight the potential of the MLP-based ensemble technique. The study contributes to a deeper understanding of thematic categories and textual features in classical Chinese poetry and offers an automated classification system for classical Chinese poems.},
+    journal = {J. Comput. Cult. Herit.},
+    month = dec,
+    articleno = {60},
+    numpages = {19},
+    keywords = {Thematic Classification, Classical Chinese Poetry, Ensemble Learning, Pre-trained Language Model}
+    }
+```