Short text classification model based on dynamic routing and CNN with attention mechanism

Qingsong Wang; Mengying Jin; Nianyin Yang

doi:10.1117/12.3004062

11 October 2023 Short text classification model based on dynamic routing and CNN with attention mechanism

Qingsong Wang, Mengying Jin, Nianyin Yang

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128001O (2023) https://doi.org/10.1117/12.3004062
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Unlike long texts, short texts can cause the problem of feature sparsity due to their short length. Although the existing deep learning-based methods alleviate this problem, the extracted semantic features are inevitably redundant, and the relationships between features are not fully considered when performing feature fusion, which in turn makes the semantics ambiguous and classification very difficult. To address the multi-feature fusion problem, we propose a Short Text Classification Model Based on Dynamic Routing and CNN with Attention Mechanism (DCAN). Firstly, we use Convolutional Neural Network (CNN) to extract text features with different granularity to enrich the semantic representation; secondly, we use attention mechanism and residual structure to fuse features with different granularity to obtain features with contextual semantic relationships, and then them into dynamic routing to obtain the probability distribution of short texts. We conducted experiments on four datasets, including AG News, MR, TREC, and SST-2. The experimental results show that DCAN has higher classification accuracy compared with most of the currently popular models.

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

Citation Download Citation

Qingsong Wang, Mengying Jin, and Nianyin Yang "Short text classification model based on dynamic routing and CNN with attention mechanism", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128001O (11 October 2023); https://doi.org/10.1117/12.3004062

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KEYWORDS

Feature extraction

Convolution

Classification systems

Semantics

Education and training

Feature fusion

Convolutional neural networks

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