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+ ---
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+ tags:
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+ - keyword-extraction
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+ language:
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+ - ind
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+ ---
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+
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+ The KEPS dataset (Mahfuzh, Soleman and Purwarianti, 2019) consists of text from Twitter
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+ discussing banking products and services and is written in the Indonesian language. A phrase
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+ containing important information is considered a keyphrase. Text may contain one or more
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+ keyphrases since important phrases can be located at different positions.
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+ - tokens: a list of string features.
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+ - seq_label: a list of classification labels, with possible values including O, B, I.
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+ The labels use Inside-Outside-Beginning (IOB) tagging.
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+
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+
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+ ## Dataset Usage
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+
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+ Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
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+
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+ ## Citation
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+
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+ ```@inproceedings{mahfuzh2019improving,
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+ title={Improving Joint Layer RNN based Keyphrase Extraction by Using Syntactical Features},
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+ author={Miftahul Mahfuzh, Sidik Soleman, and Ayu Purwarianti},
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+ booktitle={Proceedings of the 2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)},
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+ pages={1--6},
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+ year={2019},
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+ organization={IEEE}
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+ }
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+ ```
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+
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+ ## License
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+
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+ Creative Common Attribution Share-Alike 4.0 International
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+
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+ ## Homepage
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+
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+ ### NusaCatalogue
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+
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+ For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)