湖南工业大学学报2024，Vol.38Issue(1)：70-77,8.DOI:10.3969/j.issn.1673-9833.2024.01.010
基于序列增强的事件主体抽取方法
Event Subject Extraction Method Based on Sequence Enhancement
摘要
Abstract
In view of a solution of semantic deviation brought about by overfilling short sentences with fixed text length in event extraction,a sequence enhancement based event subject extraction method has thus been proposed.Specifically,an initial mapping of the fixed-length text is given to a dense vector through a pre-trained model.Subsequently,the dense vector corresponding to the text is bitwise multiplied by the custom Mask layer and SpatialDropout layer,thus obtaining the encoded output.Finally,the output is connected with BiGRU and Mask layers to get the decoded output,which is then mapped to an MLP layer to obtain the final result.This model can not only avoid the problem of overfitting the text representation in the pre-trained model,but also limit the semantic overexpression of the filled text.By using the financial field event subjects provided by CCKS 2022 as a dataset for different model reading comparative experiments,the experimental data obtained shows that the enhanced sequence with negative impact on filled text significantly improves the accuracy and F1 value of event subject recognition compared to traditional sequences.关键词
序列增强/事件主体/抽取/掩码模型Key words
sequence enhancement/event subject/extraction/masked model分类
信息技术与安全科学引用本文复制引用
沈加锐,朱艳辉,金书川,张志轩,满芳滕..基于序列增强的事件主体抽取方法[J].湖南工业大学学报,2024,38(1):70-77,8.基金项目
国家自然科学基金资助项目(62106074) （62106074）
湖南省教育厅基金资助重点项目(22A0408,21A0350) （22A0408,21A0350）
湖南省自然科学基金资助项目(2022JJ50051) （2022JJ50051）
