Hierarchical Multi-label Text Classification Method Based On Multi-level Decoupling

Abstract

In order to facilitate subsequent processing, the government hotline assigns hierarchical labels to the collected complaint and report texts. Classification of hierarchical multi-label text is a challenging task. Most previous studies regard hierarchical multi-label text classification as a flat multi-label classification problem, ignoring the constraints and connections between hierarchical labels. In this paper, we set hierarchical multi-label text classification as a sequence generation task, and propose a sequence-to-sequence-based hierarchical multi-label text classification model. Mainly use the method of multi-level decoupling to make better use of the connection between hierarchical tags, transform the constraints between tags into usable information, and help better classification. Compared with other models, the model proposed in this paper has a significant effect in the text classification of 12345 wading-related complaints and reports in Beijing.