%0 Journal Article
%T 基于Bert-BiLSTM-CRF的标讯信息提取实现<br>Implementation of Bids Information Extraction Based on Bert BiLSTM-CRF
%A 李正军
%A 涂著刚
%J Software Engineering and Applications
%P 1430-1438
%@ 2325-2278
%D 2022
%I Hans Publishing
%R 10.12677/SEA.2022.116147
%X 面对海量的标讯信息规模及复杂的数据结构，如何高效地挖掘潜在的数据价值，是能否有效实现招投标领域大数据应用的关键。本文通过大量数据标注，借助Bert-BiLSTM-CRF机器学习算法，对标讯信息的关键字段实现自动提取，有效实现标讯信息的结构化和价值化。<br />
In the face of massive scale and complex data structure of bidding information, how to efficiently tap the potential data value is the key to effectively implement big data applications in the bidding field. In this paper, with the help of Bert BiLSTM-CRF machine learning algorithm, the key fields of the banner information are automatically extracted through a large number of data annotations, effectively realizing the structure and value of the banner information.
%K Bert-BiLSTM-CRF，数据价值，命名实体识别，深度学习，数据标注<br>Bert-BiLSTM-CRF
%K Data Value
%K Named Entity Recognition
%K Deep Learning
%K Data Annotation
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=59940