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International Journal of Applied Sciences and Smart Technologies, 2021 By and large, we don't know to talk and read the territorial dialects that are spoken in our nation. So we have accepted Tamil language as it is our territorial and numerous doesn't get it.
Omprakash Yadav +4 more
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Learning label smoothing for text classification [PDF]
PeerJ Computer ScienceTraining with soft labels instead of hard labels can effectively improve the robustness and generalization of deep learning models. Label smoothing often provides uniformly distributed soft labels during the training process, whereas it does not take the
Han Ren, Yajie Zhao, Yong Zhang, Wei Sun
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Sensors, 2022 As a research hotspot in the field of natural language processing (NLP), sentiment analysis can be roughly divided into explicit sentiment analysis and implicit sentiment analysis.
Meikang Chen +4 more
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Text Classification Based on Graph Neural Networks and Dependency Parsing [PDF]
Jisuanji kexue, 2022 Text classification is a basic and important task in natural language processing.It is widely used in language processing scenarios such as news classification,topic tagging and sentiment analysis.The current text classification models generally do not ...
YANG Xu-hua, JIN Xin, TAO Jin, MAO Jian-fei
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Research on cross-language text intelligence classification method based on deep learning [PDF]
Zhihui kongzhi yu fangzhen, 2023 Text intelligence classification is the basic work in the field of intelligence analysis. At present, text intelligence classification work is usually oriented to a single language, and there are relatively few studies on cross-language text intelligence
YIN Lai-xiang, LI Zhi-qiang, LI Yuan-long
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Text classification using capsules [PDF]
Neurocomputing, 2020 This paper presents an empirical exploration of the use of capsule networks for text classification. While it has been shown that capsule networks are effective for image classification, their validity in the domain of text has not been explored. In this paper, we show that capsule networks indeed have the potential for text classification and that ...
Jaeyoung Kim +3 more
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Self-supervised Regularization for Text Classification
Transactions of the Association for Computational Linguistics, 2021 Text classification is a widely studied problem and has broad applications. In many real-world problems, the number of texts for training classification models is limited, which renders these models prone to overfitting.
Meng Zhou, Zechen Li, Pengtao Xie
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Comparison of text-image fusion models for high school diploma certificate classification
Communications in Science and Technology, 2020 File scanned documents are commonly used in this digital era. Text and image extraction of scanned documents play an important role in acquiring information. A document may contain both texts and images.
Chandra Ramadhan Atmaja Perdana +2 more
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Revisiting Text Guide, a Truncation Method for Long Text Classification
Applied Sciences, 2021 The quality of text classification has greatly improved with the introduction of deep learning, and more recently, models using attention mechanism.
Krzysztof Fiok +5 more
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A Survey on Text Classification Algorithms: From Text to Predictions
Information, 2022 In recent years, the exponential growth of digital documents has been met by rapid progress in text classification techniques. Newly proposed machine learning algorithms leverage the latest advancements in deep learning methods, allowing for the ...
Andrea Gasparetto +3 more
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