Smart Contract Classification With a Bi-LSTM Based Approach
With the number of smart contracts growing rapidly, retrieving the relevant smart contracts quickly and accurately has become an important issue. A key step for recognizing the related smart contracts is able to classify them accurately. Different from traditional text, the smart contract is compose...
Main Authors: | Gang Tian, Qibo Wang, Yi Zhao, Lantian Guo, Zhonglin Sun, Liangyu Lv |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9019682/ |
Similar Items
-
Bi-LSTM Model to Increase Accuracy in Text Classification: Combining Word2vec CNN and Attention Mechanism
by: Beakcheol Jang, et al.
Published: (2020-08-01) -
Research on Short Video Hotspot Classification Based on LDA Feature Fusion and Improved BiLSTM
by: Linhui Li, et al.
Published: (2022-11-01) -
CNN-Bi-LSTM: A Complex Environment-Oriented Cattle Behavior Classification Network Based on the Fusion of CNN and Bi-LSTM
by: Guohong Gao, et al.
Published: (2023-09-01) -
BiLSTM Model With Attention Mechanism for Sentiment Classification on Chinese Mixed Text Comments
by: Li Xiaoyan, et al.
Published: (2023-01-01) -
Self-Attention-Based BiLSTM Model for Short Text Fine-Grained Sentiment Classification
by: Jun Xie, et al.
Published: (2019-01-01)