A noise-handling method based on textual entailment model

Runyu Wu; Weimin Ni; Zelin Chen

doi:10.1117/12.3004042

11 October 2023 A noise-handling method based on textual entailment model

Runyu Wu, Weimin Ni, Zelin Chen

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128003Z (2023) https://doi.org/10.1117/12.3004042
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

In response to the high cost of obtaining high-quality annotated data, some methods have emerged that automatically extract annotated data from large-scale unlabeled datasets. However, these methods often result in noisy data, which can negatively impact the performance of models. Therefore, noise-handling methods for data have high practical value. This article proposes a novel noise-handling method based on textual entailment model and applies it to text classification tasks. Experimental results demonstrate that the proposed method performs well when the proportion of noise data in the overall dataset is relatively high, which provides a new approach for the research of noise-handling methods.

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

Citation Download Citation

Runyu Wu, Weimin Ni, and Zelin Chen "A noise-handling method based on textual entailment model", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128003Z (11 October 2023); https://doi.org/10.1117/12.3004042

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