Papers with hierarchical multi-label text classification

2 papers
Hierarchical Multi-label Classification of Text with Capsule Networks (P19-2)

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Challenge: In hierarchical multi-label classification, samples are classified into one or multiple class labels organized in a structured label hierarchy.
Approach: They apply and compare shallow capsule networks for hierarchical multi-label text classification and introduce a new real-world scenario dataset.
Outcome: The proposed model outperforms neural networks and non-neural network architectures on a real-world scenario dataset.
Hierarchical Multi-Label Classification of Scientific Documents (2022.emnlp-main)

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Challenge: Automated topic classification is a useful tool for managing scientific documents in a digital collection.
Approach: They propose a hierarchical multi-label text classification dataset with keyword labeling as an auxiliary task.
Outcome: The proposed model achieves a Macro-F1 score of 34.57% and is publicly available.

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