CCL23-Eval 任务6系统报告:基于深度学习的电信网络诈骗案件分类(System Report for CCL23-Eval Task 6: Classification of Telecom Internet Fraud Cases Based on Deep Learning)

Chenyang Li (李晨阳), Long Zhang (张龙), Zhongjie Zhao (赵中杰), Hui Guo (郭辉)


Abstract
“文本分类任务作为自然语言处理领域的基础任务,在面向电信网络诈骗领域的案件分类中扮演着至关重要的角色,对于智能化案件分析具有重大意义和深远影响。本任务的目的是对给定案件描述文本进行分类,案件文本包含对案件的经过脱敏处理后的整体描述。我们首先采用Ernie预训练模型对案件内容进行微调的方法得到每个案件的类别,再使用伪标签和模型融合方法对目前的F1值进行提升,最终在CCL23-Eval任务6电信网络诈骗案件分类评测中取得第二名的成绩,该任务的评价指标F1值为0.8628,达到了较为先进的检测效果。”
Anthology ID:
2023.ccl-3.16
Volume:
Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
Month:
August
Year:
2023
Address:
Harbin, China
Venue:
CCL
SIG:
Publisher:
Chinese Information Processing Society of China
Note:
Pages:
167–172
Language:
Chinese
URL:
https://aclanthology.org/2023.ccl-3.16
DOI:
Bibkey:
Cite (ACL):
Chenyang Li, Long Zhang, Zhongjie Zhao, and Hui Guo. 2023. CCL23-Eval 任务6系统报告:基于深度学习的电信网络诈骗案件分类(System Report for CCL23-Eval Task 6: Classification of Telecom Internet Fraud Cases Based on Deep Learning). In Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 167–172, Harbin, China. Chinese Information Processing Society of China.
Cite (Informal):
CCL23-Eval 任务6系统报告:基于深度学习的电信网络诈骗案件分类(System Report for CCL23-Eval Task 6: Classification of Telecom Internet Fraud Cases Based on Deep Learning) (Li et al., CCL 2023)
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