A transfer model for evaluating text classification models based on CNN-RBM

Zhixiong Zhang; Yun Wu

doi:10.1117/12.3026117

8 April 2024 A transfer model for evaluating text classification models based on CNN-RBM

Zhixiong Zhang, Yun Wu

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130901M (2024) https://doi.org/10.1117/12.3026117
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

With the rapid development of e-commerce industry in China, online shopping has gradually become the prevailing consumption mode in recent years. The number of comments on online commodity has also increased rapidly, but the comments are mixed and many of them are often misleading consumers’ shopping decisions, which seriously endangers the environment and market order of e-commerce. In order to extend the scope of the model and reduce the reliance on labeled samples. This paper proposes a transfer model for evaluating text classification based on CNN-RBM. Through the parameter migration of the network layer and the fine-tuning of the model hidden layer, the learned knowledge in the source domain is transferred to achieve classification of the target domain. Due to the negative transfer phenomenon in transfer learning, the performance of the model is reduced. This paper proposes an optimization algorithm based on gradient descent, which is continuously updated in the neural network according to the learning rate, so as to improve the accuracy of text classification on the target domain evaluation. In order to verify the validity of the migration model in this paper, a small number of target domain samples are used to construct the migration model, and the experimental analysis is compared with other models. The experimental results show that the migration model proposed by the text has achieved more accurate classification results on the evaluation text data set.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhixiong Zhang and Yun Wu "A transfer model for evaluating text classification models based on CNN-RBM", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130901M (8 April 2024); https://doi.org/10.1117/12.3026117

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Machine learning

Detection and tracking algorithms

Education and training

Statistical modeling

Feature extraction

Neural networks

Show All Keywords

Keywords/Phrases

Search In:

Publication Years