Recent Advances in Hierarchical Multi-label Text Classification: A Survey

• URL: http://arxiv.org/abs/2307.16265v1
• Date: Sun, 30 Jul 2023 16:13:00 GMT
• Title: Recent Advances in Hierarchical Multi-label Text Classification: A Survey
• Authors: Rundong Liu, Wenhan Liang, Weijun Luo, Yuxiang Song, He Zhang, Ruohua Xu, Yunfeng Li, Ming Liu
• Abstract summary: Hierarchical multi-label text classification aims to classify the input text into multiple labels, among which the labels are structured and hierarchical. It is a vital task in many real world applications, e.g. scientific literature archiving.
• Score: 11.709847202580505
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Hierarchical multi-label text classification aims to classify the input text into multiple labels, among which the labels are structured and hierarchical. It is a vital task in many real world applications, e.g. scientific literature archiving. In this paper, we survey the recent progress of hierarchical multi-label text classification, including the open sourced data sets, the main methods, evaluation metrics, learning strategies and the current challenges. A few future research directions are also listed for community to further improve this field.

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