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January 1, 2025International Journal of Bio-Inspired Computation

Text Classification Model Based on ELMo and Capsnets Network

Hu Yulan Qing Zhao

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Key Points

The aim is to develop a text classification model utilizing ELMo and Capsnets for improved accuracy.
Implemented a text classification model combining ELMo embeddings and Capsnets architecture.
Conducted experiments on benchmark datasets to validate model performance.
Analyzed results using standard metrics in natural language processing.
The ELMo and Capsnets model achieved an accuracy rate of 92% on the test dataset.
Demonstrated a 15% improvement in classification accuracy over traditional methods.
Highlighted the potential for further enhancements in text processing tasks.

Implication

Explores text classification effectiveness in AI systems, suggesting improvements for model accuracy.

Abstract

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Cite This Study

Yulan et al. (2025) studied this question.

synapsesocial.com/papers/6a2e46b3b1cc60ccdea8b56a https://doi.org/10.1504/ijbic.2025.10079138

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