摘要
本次研究针对文本数据处理工作中的文本分类项目提出了一套基于Attention-Based LSTM算法的分类模型,根据Attention-Model的基本原理对Attention-Based LSTM算法数据处理方式进行了详细介绍。最后将Attention-Based LSTM算法应用于来自国内外主流门户网站文本数据的分类处理工作。经统计分析发现,Attention-Based LSTM算法相比于常规LSTM算法和Bi-LSTM体现出了更高的分类准确率水平,在文本数据处理方面具有一定的应用价值。
This research proposes a classification model based on attention based LSTM algorithm for text classification in text data processing,and introduces the data processing method of attention based LSTM algorithm in detail according to the basic principle of attention model.Finally,the attention based LSTM algorithm is applied to the text data classification from the domestic and foreign mainstream portals.Through statistical analysis,it is found that the attention based LSTM algorithm has higher classification accuracy than the conventional LSTM algorithm and Bi LSTM algorithm,and has certain application value in text data processing.
作者
黄阿娜
HUANG A-na(Xianyang Vocational&Technical College,Xianyang 712000 China)
出处
《自动化技术与应用》
2022年第8期169-171,共3页
Techniques of Automation and Applications
