融合标签关系的法律文本多标签分类方法

doi:10.16451/j.cnki.issn1003-6059.202202009

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Abstract

With the rapid development of big data technology, multi-label text classification spawns many applications in the judicial field. There are multiple element labels in legal texts, and the labels are interdependent or correlated. Accurate identification of these labels requires the support of multi-label classification method. In this paper, a multi-label classification method of legal texts with fusion of label relations(MLC-FLR) is proposed. A graph convolution network model is utilized to capture the dependency relationship between labels by constructing the co-occurrence matrix of labels. The label attention mechanism is employed to calculate the degrees of correlation between a legal text and each label word, and the legal text semantic representation of a specific label can be obtained. Finally, the comprehensive representation of a text for multi-label classification is carried out by combining the dependency relationship and the legal text semantic representation of a specific label. Experimental results on the legal text datasets show that MLC-FLR achieves better classification accuracy and stability.

Key words： Multi-label Classification Document Representation Graph Convolutional Neural Network Label Attention Mechanism Label Relation

Received: 07 May 2021

ZTFLH:

TP 391

Fund:

Supported by National Natural Science Foundation of China(No.62072294,62076158,62106130,61906112), Key Research and Development Program of Shanxi Province(No.201803D421024), Graduate Innovation Programs of Shanxi Province(No.2021Y149)

Corresponding Authors: LI Deyu, Ph.D., professor. His research interests include gra-nular computing and machine learning.

About author:: SONG Zeyu, master student. His research interests include text mining and natural language processing.LI Yang, Ph.D., lecturer. Her research interests include text sentiment analysis.WANG Suge, Ph.D., professor. Her research interests include natural language processing and sentiment analysis

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	SONG Zeyu
	LI Yang
	LI Deyu
	WANG Suge

Cite this article:

SONG Zeyu,LI Yang,LI Deyu等. Multi-label Classification of Legal Text with Fusion of Label Relations[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(2): 185-192.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202202009 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I2/185

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