Al Ani, M. M., Omar, N., & Nafea, A. A. (2021). A hybrid method of long short term memory and auto encoder architectures for sarcasm detection. Journal of Computer Science, 17(11), 1093–1098. https://doi.org/10.3844/jcssp.2021.1093.1098

Alahakoon, D., & Tan, K. C. (2021). Data preprocessing in machine learning: A review. Information Fusion, 73, 1–13. https://doi.org/10.1016/j.inffus.2021.02.003

Alexander, A., & Widdows, D. (2023). Quantum text encoding for classification tasks. IEEE/ACM SEC.

Bamman, D., & Smith, N. (2021). Contextualized sarcasm detection on Twitter. Proceedings of the International AAAI Conference on Web and Social Media, 9(1), 574–577. https://doi.org/10.1609/ icwsm.v9i1.14655

Babanejad, M., Vechtomova, O., & Mohammad, S. (2020). Affective and contextual embeddings for sarcasm detection. Proceedings of COLING, 754–765. https://doi.org/10.18653/v1/2020.coling- main.20

Cerezo, M., Verdon, G., Huang, H.-Y., Cincio, L., & Coles, P. J. (2023). Challenges and opportunities in quantum machine learning. arXiv preprint.

Chatterjee, N., Das, A., & Bandyopadhyay, S. (2023). A BiLSTM variational autoencoder framework for sarcasm detection under class imbalance. Soft Computing, 27, 6543–6558. https://doi. org/10.1007/s00500-023-07956-w

Ghosh, A., & Veale, T. (2016). Fracking sarcasm using neural network. WASSA Proceedings, 161– 169. https://doi.org/10.18653/v1/W16-0425

Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735–1780.

Mamatov, N. S., Turg‘unova, N. M., Turg‘unov, B. X., & Samijonov, B. N. (2024). Algorithm for analysis of texts in Uzbek language. In Artficial Intelligence and Information Technologies (pp. 511– 515). CRC Press.

Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv:1301.3781. https://doi.org/10.48550/arXiv.1301.3781

Nguyen, T., Sipola, T., & Hautamäki, J. (2024). Machine learning applications of quantum computing: A review. arXiv preprint. https://doi.org/10.34190/eccws.23.1.2258

Niyozmatova, N. A., & Turg‘unova, N. M. (2025). Matnlarni vektorlashni tf_idf kvant algoritmi [TF-IDF quantum algorithm for text vectorization]. Digital Transformation and Artificial Intelligence, 3(4), 1–11.

Poslavskaya, Ye., & Korolev, A. (2023). Encoding categorial data: Is there anything ‘hotter’ than one-hot encoding? Huawei Novosibirsk Research Center. https://doi.org/10.48550/arXiv.2312.16930

Rezvan, M. R., Sorkhi, A. G., Pirgazi, J., & Kallehbasti, M. M. P. (2024). AdvanceSplice: Integrating N-gram one-hot encoding and ensemble modeling for enhanced accuracy. Biomedical Signal Processing and Control, 92, 106017. https://doi.org/10.1016/j.bspc.2024.106017

Widdows, D., Aboumrad, W., Kim, D., Ray, S., & Mei, J. (2024). Quantum natural language processing. KI – Künstliche Intelligenz [AI – Artificial Intelligence], 38, 293–310.

Wu, S., Li, J., Zhang, P., & Zhang, Y. (2021). Natural language processing meets quantum physics: A survey and categorization. EMNLP.