计算机与数字工程2024，Vol.52Issue(6)：1795-1801,7.DOI:10.3969/j.issn.1672-9722.2024.06.034
基于注意力机制与PCNN的地质关系抽取方法
Geological Relation Extraction Method Based on Attention Mechanism and PCNN
孙琛皓 1庄子浩 1焦守龙1
作者信息
- 1. 中国石油大学(华东)计算机科学与技术学院 青岛 266580
- 折叠
摘要
Abstract
Relation extraction in the geological domain is of great significance to the intelligent analysis of geological data and the construction of knowledge graph of Geology.To solve the problems of missing data sets and the difficulty in feature extraction for relation extraction tasks of the geological domain,this paper builds a large-scale relation extraction data set in geological domain based on the idea of distant supervision,and proposes a distant supervision relation extraction model which combines attention mechanism and piecewise convolutional neural network(PCNN).The model in this paper uses the piecewise convolutional neural network to automatically extract the semantic features of the training instances.At the same time,the segmented attention mecha-nism is added to the piecewise convolutional neural network to highlight important segments in the instance,which strengthens the model's ability to extract important features in training instances.In addition,a sentence-level attention mechanism is introduced in-to this model to reduce the impact of incorrectly labeled data due to the distant supervision.The experimental results on the relation extraction data set in the geological field based on distant supervision show that the precision,recall,and F1 value of this model are all higher than other baseline models,which illustrates that the method has better relation extraction capabilities.关键词
关系抽取/远程监督/深度学习/地质领域/注意力机制Key words
relation extraction/distant supervision/deep learning/geological field/attention mechanism分类
信息技术与安全科学引用本文复制引用
孙琛皓,庄子浩,焦守龙..基于注意力机制与PCNN的地质关系抽取方法[J].计算机与数字工程,2024,52(6):1795-1801,7.
