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Research on multi-label short text categorization method for online education under deep learning

  
19 mar 2025
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Wang, C., Nulty, P., & Lillis, D. (2020, December). A comparative study on word embeddings in deep learning for text classification. In Proceedings of the 4th international conference on natural language processing and information retrieval (pp. 37-46). Wang C. Nulty P. Lillis D. ( 2020 , December ). A comparative study on word embeddings in deep learning for text classification . In Proceedings of the 4th international conference on natural language processing and information retrieval (pp. 37 - 46 ). Search in Google Scholar

Guo, B., Han, S., Han, X., Huang, H., & Lu, T. (2021, May). Label confusion learning to enhance text classification models. In Proceedings of the AAAI conference on artificial intelligence (Vol. 35, No. 14, pp. 12929-12936). Guo B. Han S. Han X. Huang H. Lu T. ( 2021 , May ). Label confusion learning to enhance text classification models . In Proceedings of the AAAI conference on artificial intelligence (Vol. 35 , No. 14 , pp. 12929 - 12936 ). Search in Google Scholar

Liu, W., Pang, J., Li, N., Zhou, X., & Yue, F. (2021). Research on multi-label text classification method based on tALBERT-CNN. International Journal of Computational Intelligence Systems, 14(1), 201. Liu W. Pang J. Li N. Zhou X. Yue F. ( 2021 ). Research on multi-label text classification method based on tALBERT-CNN . International Journal of Computational Intelligence Systems , 14 ( 1 ), 201 . Search in Google Scholar

Sajid, N. A., Rahman, A., Ahmad, M., Musleh, D., Basheer Ahmed, M. I., Alassaf, R., … & AlKhulaifi, D. (2023). Single vs. multi-label: The issues, challenges and insights of contemporary classification schemes. Applied Sciences, 13(11), 6804. Sajid N. A. Rahman A. Ahmad M. Musleh D. Basheer Ahmed M. I. Alassaf R. AlKhulaifi D. ( 2023 ). Single vs . multi-label: The issues, challenges and insights of contemporary classification schemes. Applied Sciences , 13 ( 11 ), 6804 . Search in Google Scholar

Li, Q., Peng, H., Li, J., Xia, C., Yang, R., Sun, L., … & He, L. (2022). A survey on text classification: From traditional to deep learning. ACM Transactions on Intelligent Systems and Technology (TIST), 13(2), 1-41. Li Q. Peng H. Li J. Xia C. Yang R. Sun L. He L. ( 2022 ). A survey on text classification: From traditional to deep learning . ACM Transactions on Intelligent Systems and Technology (TIST) , 13 ( 2 ), 1 - 41 . Search in Google Scholar

Jindal, R. (2018, September). A novel method for efficient multi-label text categorization of research articles. In 2018 International Conference on Computing, Power and Communication Technologies (GUCON) (pp. 333-336). IEEE. Jindal R. ( 2018 , September ). A novel method for efficient multi-label text categorization of research articles . In 2018 International Conference on Computing, Power and Communication Technologies (GUCON) (pp. 333 - 336 ). IEEE . Search in Google Scholar

Parlak, B. (2023). Ensemble feature selection for single-label text classification: a comprehensive analytical study. Neural Computing and Applications, 35(26), 19235-19251. Parlak B. ( 2023 ). Ensemble feature selection for single-label text classification: a comprehensive analytical study . Neural Computing and Applications , 35 ( 26 ), 19235 - 19251 . Search in Google Scholar

Song, R., Liu, Z., Chen, X., An, H., Zhang, Z., Wang, X., & Xu, H. (2023). Label prompt for multi-label text classification. Applied Intelligence, 53(8), 8761-8775. Song R. Liu Z. Chen X. An H. Zhang Z. Wang X. Xu H. ( 2023 ). Label prompt for multi-label text classification . Applied Intelligence , 53 ( 8 ), 8761 - 8775 . Search in Google Scholar

Bogatinovski, J., Todorovski, L., Džeroski, S., & Kocev, D. (2022). Comprehensive comparative study of multi-label classification methods. Expert Systems with Applications, 203, 117215. Bogatinovski J. Todorovski L. Džeroski S. Kocev D. ( 2022 ). Comprehensive comparative study of multi-label classification methods . Expert Systems with Applications , 203 , 117215 . Search in Google Scholar

Yuan, L., Xu, X., Sun, P., Yu, H. P., Wei, Y. Z., & Zhou, J. J. (2024). Research of multi-label text classification based on label attention and correlation networks. PloS one, 19(9), e0311305. Yuan L. Xu X. Sun P. Yu H. P. Wei Y. Z. Zhou J. J. ( 2024 ). Research of multi-label text classification based on label attention and correlation networks . PloS one , 19 ( 9 ), e0311305 . Search in Google Scholar

Azarbonyad, H., Dehghani, M., Marx, M., & Kamps, J. (2021). Learning to rank for multi-label text classification: Combining different sources of information. Natural Language Engineering, 27(1), 89-111. Azarbonyad H. Dehghani M. Marx M. Kamps J. ( 2021 ). Learning to rank for multi-label text classification: Combining different sources of information . Natural Language Engineering , 27 ( 1 ), 89 - 111 . Search in Google Scholar

Chen, Z., & Ren, J. (2021). Multi-label text classification with latent word-wise label information. Applied Intelligence, 51(2), 966-979. Chen Z. Ren J. ( 2021 ). Multi-label text classification with latent word-wise label information . Applied Intelligence , 51 ( 2 ), 966 - 979 . Search in Google Scholar

Goudjil, M., Koudil, M., Bedda, M., & Ghoggali, N. (2018). A novel active learning method using SVM for text classification. International Journal of Automation and Computing, 15, 290-298. Goudjil M. Koudil M. Bedda M. Ghoggali N. ( 2018 ). A novel active learning method using SVM for text classification . International Journal of Automation and Computing , 15 , 290 - 298 . Search in Google Scholar

Dhingra, M., Dhabliya, D., Dubey, M. K., Gupta, A., & Reddy, D. H. (2022, December). A Review on Comparison of Machine Learning Algorithms for Text Classification. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 1818-1823). IEEE. Dhingra M. Dhabliya D. Dubey M. K. Gupta A. Reddy D. H. ( 2022 , December ). A Review on Comparison of Machine Learning Algorithms for Text Classification . In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 1818 - 1823 ). IEEE . Search in Google Scholar

Budhiraja, M. (2017, June). Multi label text classification for un-trained data through supervised learning. In 2017 International Conference on Intelligent Computing and Control (I2C2) (pp. 1-3). IEEE. Budhiraja M. ( 2017 , June ). Multi label text classification for un-trained data through supervised learning . In 2017 International Conference on Intelligent Computing and Control (I2C2) (pp. 1 - 3 ). IEEE . Search in Google Scholar

Chen, X., Cheng, J., Liu, J., Xu, W., Hua, S., Tang, Z., & Sheng, V. S. (2022, July). A survey of multi-label text classification based on deep learning. In International Conference on Adaptive and Intelligent Systems (pp. 443-456). Cham: Springer International Publishing. Chen X. Cheng J. Liu J. Xu W. Hua S. Tang Z. Sheng V. S. ( 2022 , July ). A survey of multi-label text classification based on deep learning . In International Conference on Adaptive and Intelligent Systems (pp. 443 - 456 ). Cham : Springer International Publishing . Search in Google Scholar

Mohammed, H. H., Dogdu, E., Görür, A. K., & Choupani, R. (2020, December). Multi-label classification of text documents using deep learning. In 2020 IEEE International Conference on Big Data (Big Data) (pp. 4681-4689). IEEE. Mohammed H. H. Dogdu E. Görür A. K. Choupani R. ( 2020 , December ). Multi-label classification of text documents using deep learning . In 2020 IEEE International Conference on Big Data (Big Data) (pp. 4681 - 4689 ). IEEE . Search in Google Scholar

Liu, X., Shi, T., Zhou, G., Liu, M., Yin, Z., Yin, L., & Zheng, W. (2023). Emotion classification for short texts: an improved multi-label method. Humanities and Social Sciences Communications, 10(1), 1-9. Liu X. Shi T. Zhou G. Liu M. Yin Z. Yin L. Zheng W. ( 2023 ). Emotion classification for short texts: an improved multi-label method . Humanities and Social Sciences Communications , 10 ( 1 ), 1 - 9 . Search in Google Scholar

Shimura, K., Li, J., & Fukumoto, F. (2018). HFT-CNN: Learning hierarchical category structure for multi-label short text categorization. In Proceedings of the 2018 conference on empirical methods in natural language processing (pp. 811-816). Shimura K. Li J. Fukumoto F. ( 2018 ). HFT-CNN: Learning hierarchical category structure for multi-label short text categorization . In Proceedings of the 2018 conference on empirical methods in natural language processing (pp. 811 - 816 ). Search in Google Scholar

Maragheh, H. K., Gharehchopogh, F. S., Majidzadeh, K., & Sangar, A. B. (2024). A Hybrid Model Based on Convolutional Neural Network and Long Short-Term Memory for Multi-label Text Classification. Neural Processing Letters, 56(2), 42. Maragheh H. K. Gharehchopogh F. S. Majidzadeh K. Sangar A. B. ( 2024 ). A Hybrid Model Based on Convolutional Neural Network and Long Short-Term Memory for Multi-label Text Classification . Neural Processing Letters , 56 ( 2 ), 42 . Search in Google Scholar

Almeida, A. M., Cerri, R., Paraiso, E. C., Mantovani, R. G., & Junior, S. B. (2018). Applying multi-label techniques in emotion identification of short texts. Neurocomputing, 320, 35-46. Almeida A. M. Cerri R. Paraiso E. C. Mantovani R. G. Junior S. B. ( 2018 ). Applying multi-label techniques in emotion identification of short texts . Neurocomputing , 320 , 35 - 46 . Search in Google Scholar

Liu, H., Chen, G., Li, P., Zhao, P., & Wu, X. (2021). Multi-label text classification via joint learning from label embedding and label correlation. Neurocomputing, 460, 385-398. Liu H. Chen G. Li P. Zhao P. Wu X. ( 2021 ). Multi-label text classification via joint learning from label embedding and label correlation . Neurocomputing , 460 , 385 - 398 . Search in Google Scholar

Gong, J., Teng, Z., Teng, Q., Zhang, H., Du, L., Chen, S., … & Ma, H. (2020). Hierarchical graph transformer-based deep learning model for large-scale multi-label text classification. IEEE Access, 8, 30885-30896. Gong J. Teng Z. Teng Q. Zhang H. Du L. Chen S. Ma H. ( 2020 ). Hierarchical graph transformer-based deep learning model for large-scale multi-label text classification . IEEE Access , 8 , 30885 - 30896 . Search in Google Scholar

Khataei Maragheh, H., Gharehchopogh, F. S., Majidzadeh, K., & Sangar, A. B. (2022). A new hybrid based on long short-term memory network with spotted hyena optimization algorithm for multi-label text classification. Mathematics, 10(3), 488. Khataei Maragheh H. Gharehchopogh F. S. Majidzadeh K. Sangar A. B. ( 2022 ). A new hybrid based on long short-term memory network with spotted hyena optimization algorithm for multi-label text classification . Mathematics , 10 ( 3 ), 488 . Search in Google Scholar

Jiangxin Shi,Tong Wei & Yufeng Li. (2024). Residual diverse ensemble for long-tailed multi-label text classification. Science China Information Sciences(11),212102-212102. Jiangxin Shi Tong Wei Yufeng Li . ( 2024 ). Residual diverse ensemble for long-tailed multi-label text classification . Science China Information Sciences(11) , 212102 - 212102 . Search in Google Scholar

Amuguleng Wang,Yilagui Qi & Dahu Baiyila. (2025). C-BERT: A Mongolian reverse dictionary based on fused lexical semantic clustering and BERT. Alexandria Engineering Journal385-395. Amuguleng Wang Yilagui Qi Dahu Baiyila . ( 2025 ). C-BERT: A Mongolian reverse dictionary based on fused lexical semantic clustering and BERT . Alexandria Engineering Journal 385 - 395 . Search in Google Scholar

Zhou Xuemei,Wang Qianlin,Zhang Yunbo,Li Boqian & Zhao Xiaochi. (2025). Short-Term Bus Passenger Flow Prediction Based on BiLSTM Neural Network. Journal of Transportation Engineering, Part A: Systems(1). Zhou Xuemei Wang Qianlin Zhang Yunbo Li Boqian Zhao Xiaochi . ( 2025 ). Short-Term Bus Passenger Flow Prediction Based on BiLSTM Neural Network . Journal of Transportation Engineering, Part A: Systems(1) . Search in Google Scholar

Bo Zhang,Li Xu,Ke Hao Liu,Ru Yang,Mao Zhen Li & Xiao Yang Guo. (2025). Piecewise convolutional neural network relation extraction with self-attention mechanism. Pattern Recognition111083-111083. Bo Zhang Li Xu Ke Hao Liu Ru Yang Mao Zhen Li Xiao Yang Guo . ( 2025 ). Piecewise convolutional neural network relation extraction with self-attention mechanism . Pattern Recognition1 11083 - 111083 . Search in Google Scholar

Yunpeng Xiong,Guolian Chen & Junkuo Cao. (2024). Research on Public Service Request Text Classification Based on BERT-BiLSTM-CNN Feature Fusion. Applied Sciences(14),6282-6282. Yunpeng Xiong Guolian Chen Junkuo Cao . ( 2024 ). Research on Public Service Request Text Classification Based on BERT-BiLSTM-CNN Feature Fusion . Applied Sciences(14) , 6282 - 6282 . Search in Google Scholar

Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro