Multi-source combined transfer learning for text classification

Bingbing Song; Jianhan Pan; Qiaoli Qu; Sijing Chen

doi:10.1117/12.3004780

9 October 2023 Multi-source combined transfer learning for text classification

Bingbing Song, Jianhan Pan, Qiaoli Qu, Sijing Chen

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127910D (2023) https://doi.org/10.1117/12.3004780
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

The objective of transfer learning is to learn well-established knowledge from label-rich training data to handle learning tasks on the target domain, where the labeled samples can be hardly collected and the data distribution is different from that of the training data. Nowadays, the label information in the target domain may exist in multiple different source domains, but none of which can cover all the information. To make use of the imperfect source domains, many novel transfer learning algorithms explore potential properties among them to improve the completeness of transferred knowledge. However, these works only build on the original source domains, limiting the possibility to uncover additional supplementary information. In this paper, we propose novel multi-source combined transfer learning(MSCTL). MSCTL first replaces original source domains with a new training set space which can provide richer latent information by correlating multiple source domains. Then, through a triplex-complementary strategy, MSCTL extracts and integrates threefold concepts from the space to make the knowledge complementary and integral. Furthermore, we design MSCTL as an optimization problem and provide an iterative algorithm to solve it. Finally, massive experiments are performed to verify the effectiveness of our method.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bingbing Song, Jianhan Pan, Qiaoli Qu, and Sijing Chen "Multi-source combined transfer learning for text classification", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127910D (9 October 2023); https://doi.org/10.1117/12.3004780

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