Three TextCNN-based sub-classifiers for Japanese text classification are designed. •. A Bagging ensemble learning model is proposed to combine three ...
In this paper, we aim at improving Japanese text classification using TextCNN-based ensemble learning model. Specifically, we first construct three ...
Semantic Scholar extracted view of "TextCNN-based ensemble learning model for Japanese Text Multi-classification" by Hua Chen et al.
This paper mainly focuses on using ALBERT-TextCNN for Japanese text classification. First, the data files from Japanese Wikipedia pages are collected and then ...
Sep 20, 2024 · TextCNN-based ensemble learning model for Japanese Text Multi-classification. Abstract. In this paper, we aim at improving Japanese text ...
Sep 30, 2024 · In this study, we proposed MuTCELM, a novel Multi-TextCNN-based Ensemble Learning Model optimized for text classification tasks across multiple ...
Missing: Japanese | Show results with:Japanese
Oct 18, 2024 · [53] proposed an ensemble learning model based on TextCNN, which combines ALBERT, RoBERTa, and DistilBERT to extract textual features and ...
(PDF) MuTCELM: An optimal multi-TextCNN-based ensemble ...
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Oct 4, 2024 · ... proposed MuTCELM, a novel Multi-TextCNN-based Ensemble Learning Model optimized for text classification tasks. Heliyon 10 (2024) e38515. 19.
Missing: Japanese | Show results with:Japanese
Machine learning and rule-based embedding techniques for classifying text documents · A Study on Japanese Text Multi-classification with ALBERT-TextCNN · Text ...