SaiedAlshahrani
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README.md
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@@ -149,14 +149,15 @@ We release the heuristically filtered, manually processed, and automatically cla
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This dataset is introduced in a research paper titled "[***Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition***](https://arxiv.org/abs/2404.00565)", which is **accepted** at [LREC-COLING 2024](https://lrec-coling-2024.org/): [The 6th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT6)](https://osact-lrec.github.io/), and is currently released under an MIT license.
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## Dataset Subsets:
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1. **Balanced**: A balanced subset of the dataset comprised 20K (10K for each class) and was split in the ratio of 80:20 for training and testing. This subset was filtered and processed using selected heuristic rules.
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2. **Unbalanced**: An unbalanced subset of the dataset comprised 166K and was split in the ratio of 80:20 for training and testing. This subset is the rest of the filtered and processed articles using selected heuristic rules.
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3. **Uncategorized**: Another unbalanced subset of the dataset comprised 569K and was split in the ratio of 80:20 for training and testing, but this was classified automatically using the `XGBoost` classifier trained using the balanced subset.
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🚧 Under Construction
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@article{alshahrani2024leveraging,
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title={Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition},
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author={Saied Alshahrani and Hesham Haroon and Ali Elfilali and Mariama Njie and Jeanna Matthews},
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journal={arXiv preprint arXiv:2404.00565},
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url={https://arxiv.org/abs/2404.00565}
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}
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```
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This dataset is introduced in a research paper titled "[***Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition***](https://arxiv.org/abs/2404.00565)", which is **accepted** at [LREC-COLING 2024](https://lrec-coling-2024.org/): [The 6th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT6)](https://osact-lrec.github.io/), and is currently released under an MIT license.
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## Dataset Subsets:
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1. **Balanced**: A balanced subset of the dataset comprised 20K (10K for each class) and was split in the ratio of 80:20 for training and testing. This subset was filtered and processed using selected heuristic rules.
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2. **Unbalanced**: An unbalanced subset of the dataset comprised 166K and was split in the ratio of 80:20 for training and testing. This subset is the rest of the filtered and processed articles using selected heuristic rules.
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3. **Uncategorized**: Another unbalanced subset of the dataset comprised 569K and was split in the ratio of 80:20 for training and testing, but this was classified automatically using the `XGBoost` classifier trained using the balanced subset.
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## Please Cite:
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```
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@article{alshahrani2024leveraging,
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title={Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition},
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author={Saied Alshahrani and Hesham Haroon and Ali Elfilali and Mariama Njie and Jeanna Matthews},
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journal={arXiv preprint arXiv:2404.00565},
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url={https://arxiv.org/abs/2404.00565}
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}
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```
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