Sentiment Analysis for Video on Demand Application User Satisfaction with Long Short Term Memory Model

Gina Khayatun Nufus; Mustafid Mustafid; Rahmat Gernowo

doi:10.1051/e3sconf/202131705031

All issues

Volume 317 (2021)

E3S Web Conf., 317 (2021) 05031

References

Open Access

Issue		E3S Web Conf. Volume 317, 2021 The 6^th International Conference on Energy, Environment, Epidemiology, and Information System (ICENIS 2021)


Article Number		05031
Number of page(s)		6
Section		Information System Management and Environment
DOI		https://doi.org/10.1051/e3sconf/202131705031
Published online		05 November 2021

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[1] Minaee, S., Kalchbrenner, N., Cambria, E., Nikzad, N., Chenaghlu, M., dan Gao, J., 2020, Deep Learning Based Text Classification: A Comprehensive Review, 1 (1), 1–42. (2020) [Google Scholar]

[2] Cai, Y., Huang, Q., Lin, Z., Xu, J., Chen, Z., dan Li, Q., 2020, Recurrent neural network with pooling operation and attention mechanism for sentiment analysis: A multi-task learning approach, Knowledge-Based Systems 203105856. (2020) [Google Scholar]

[3] Pascanu, R., Mikolov, T., dan Bengio, Y., 2013, On the difficulty of training recurrent neural networks, 30th International Conference on Machine Learning, ICML 2013 (PART 3), 2347–2355. (2013) [Google Scholar]

[4] Wang, J., Peng, B., dan Zhang, X., 2018, Using a stacked residual LSTM model for sentiment intensity prediction, Neurocomputing 32293–101. (2018) [Google Scholar]

[5] Rao, G., Huang, W., Feng, Z., dan Cong, Q., 2018, LSTM with sentence representations for document-level sentiment classification, Neurocomputing 30849–57. (2018) [Google Scholar]

[6] Mowlaei, M.E., Abadeh, A.E., dan Keshavarz, H., 2020, Aspect-based sentiment analysis using adaptive aspect-based lexicons, Expert Systems with Applications 148113234. (2020) [Google Scholar]

[7] Valentiny, C., 2018, Brand Monitoring. In L. A. Schintler & C. L. McNeely (ed.) Encyclopedia of Big Data, hal. 1–4, Springer International Publishing, Cham. (2018) [Google Scholar]

[8] Sreesurya, I., Rathi, H., Jain, P., dan Jain, K.M., 2020, Hypex: A Tool for Extracting Business Intelligence from Sentiment Analysis using Enhanced LSTM, Multimedia Tools and Applications 35641–35663. (2020) [Google Scholar]

[9] Mikolov, T., Sutskever, I., Chen, K., Corrado, G., dan Dean, J., 2013, Distributed representations ofwords and phrases and their compositionality, Advances in Neural Information Processing Systems1–9. (2013) [Google Scholar]

[10] Mikolov, T., Chen, K., Corrado, G., dan Dean, J., 2013, Efficient estimation of word representations in vector space, 1st International Conference on Learning Representations, ICLR 2013 - Workshop Track Proceedings1–12. (2013) [Google Scholar]

[11] Al-jabery, K.K., Obafemi-Ajayi,T., Olbricht, G.R., dan Wunsch II, D.C., 2020, Data preprocessing Computational Learning Approaches to Data Analytics in Biomedical Application,7–27. (2020) [Google Scholar]