Open Access
Issue
ITM Web Conf.
Volume 53, 2023
2nd International Conference on Data Science and Intelligent Applications (ICDSIA-2023)
Article Number 02006
Number of page(s) 9
Section Machine Learning / Deep Learning
DOI https://doi.org/10.1051/itmconf/20235302006
Published online 01 June 2023
  1. B. Pang, L. Lee, Found. Trends Inf. Retr. 2, 1–2, 1-135 (2008). [CrossRef] [Google Scholar]
  2. P. Domingos, Metacost: A general method for making classifiers cost-sensitive, in Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, 15-18 August 1999, San Diego California USA (1999) [Google Scholar]
  3. T. Joachims, Text categorization with support vector machines: Learning with many relevant features, in 10th European Conference on Machine Learning, Berlin, Heidelberg, 21-23 April 1998, Chemnitz, Germany (1998) [Google Scholar]
  4. Y. Kim. Convolutional neural networks for sentence classification, in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 25-29 October 2014, Doha, Qatar (2014) [Google Scholar]
  5. A. L. Maas, R. E. Daly, P. T. Pham, D. Huang, A. Y. Ng, C. Potts, Learning word vectors for sentiment analysis, in Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 19-24 June 2011, Portland, Oregon, USA (2011) [Google Scholar]
  6. R. Socher, A. Perelygin, J. Y. Wu, J. Chuang, C. D. Manning, A. Y. Ng, C. Potts, Recursive deep models for semantic compositionality over a sentiment treebank, in Proceedings of the 2013 conference on empirical methods in natural language processing, 18-21 October 2013, Seattle, Washington, USA (2013) [Google Scholar]
  7. K. Tai, R. Socher, C. D. Manning, Improved semantic representations from treestructured long short-term memory networks, in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, 26-31 July 2015, lBeijing, China (2015). [Google Scholar]
  8. Y. Mao, Y. Zhang, L. Jiao, H. Zhang, Electronics 11, 12, 1906 (2022) [CrossRef] [Google Scholar]
  9. S. Wang, C. D. Manning, Baselines and bigrams: Simple, good sentiment and topic classification. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, 8-14 July 2012, Jeju Island, Korea (2012). [Google Scholar]
  10. L. Adela. M. Ulfeta, Comp. Sci. and Info Sys. 16.13-13 (2018) [Google Scholar]
  11. M. Joshi, J. Wiebe, M. Ringuette, Sarcasm in twitter: A closer look, in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 9-11 September 2017, Copenhagen, Denmark (2017) [Google Scholar]
  12. Y. Zhou, X. Chen, L. Huang, Incorporating idiomatic expressions into sentiment analysis, in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 9-11 September 2017, Copenhagen, Denmark (2017) [Google Scholar]
  13. J. Devlin, M. W. Chang, K. Lee, K. Toutanova, BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2-7 June 2019, Minneapolis, Minnesota (2019) [Google Scholar]
  14. A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, I. Sutskever, OpenAI, 1, 8(2019) [Google Scholar]
  15. Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, V. Stoyanov, Cornell University, arXiv preprint arXiv:1907.11692, (2019) [Google Scholar]
  16. Y. Cui, W. Che, T. Liu, B. Qin, Z. Yang, IEEE/ACM Trans. Audio., Speech, and Language Proc. (TASLP), 29, (2021) [Google Scholar]
  17. X. Sun, C. Tan, Z. Liu, Cornell University, arXiv preprint arXiv:1903.09868 (2019) [Google Scholar]
  18. X. Jiang, C. Song, Y. Xu, Y. Li, Y. Peng, Peer J Comput. Sci. 8, 18, e1005 (2022) [CrossRef] [Google Scholar]
  19. R. Kiros, R. Salakhutdinov, R. Zemel, Multimodal neural language models, in Proceedings of 31st International Conference on Machine Learning Research (PMLR), 21-16 June 2014, Beijing, China (2014) [Google Scholar]
  20. Q. You, W. Li, T. Liu, Image-text joint embedding for sentiment analysis, in Proceedings of the 2016 ACM on International Conference on Multimodal Interaction, 12-16 November 2016, Tokyo, Japan (2016) [Google Scholar]
  21. https://www.kaggle.com/datasets/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews retrieved on 25 March 2023, 10.15 Hrs. [Google Scholar]

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