A method to solve unbalanced multi-label text classification in practical projects by introducing association information between classes

Yi Zhou; Yipu Qin; Peng Zhang; Jian Li; Aizhi Wu; Deyi Shi; Yunxi Liu; Zheng Ji; Mingyuan Pan; Xinbo Ai

doi:10.1117/12.2658860

20 October 2022 A method to solve unbalanced multi-label text classification in practical projects by introducing association information between classes

Yi Zhou, Yipu Qin, Peng Zhang, Jian Li, Aizhi Wu, Deyi Shi, Yunxi Liu, Zheng Ji, Mingyuan Pan, Xinbo Ai

Author Affiliations +

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 1245134 (2022) https://doi.org/10.1117/12.2658860
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

Training with more data has always been an effective and convenient way of improving performance in the deep learning era. Therefore, in practical engineering projects, data is generally collected as much as possible. However, as data volume and class size increase, maintaining a balanced dataset across a number of classes is challenging because data are always long-tailed in practical engineering projects. As a consequence, the key of the practical deep learning application is to design solutions to solve the long tail distribution problem according to the characteristics of specific projects. At present, many existing methods are often not designed according to actual engineering problems, and there is a certain gap with the actual application scenarios. In this paper, we will design a strategy based on the actual application scenarios and solve the imbalance distribution problem in practical engineering projects by adjusting the classifier according to the data.

Citation Download Citation

Yi Zhou, Yipu Qin, Peng Zhang, Jian Li, Aizhi Wu, Deyi Shi, Yunxi Liu, Zheng Ji, Mingyuan Pan, and Xinbo Ai "A method to solve unbalanced multi-label text classification in practical projects by introducing association information between classes", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 1245134 (20 October 2022); https://doi.org/10.1117/12.2658860

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