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Expert Syst. Appl., 40, 17, 6758–6765, 2013.

      7. Zhang, W., Ding, G., Chen, L., Li, C., & Zhang, C. (2013). Generating virtual ratings from chinese reviews to augment online recommendations. ACM Transactions on intelligent systems and technology (TIST), 4(1), 1–17.

      8. Bauman, K., Liu, B., Tuzhilin, A., Aspect based recommendations: Recommending items with the most valuable aspects based on user reviews, in: Proc. 23rd ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, pp. 717–725, 2017.

      9. Akhtar, N., Zubair, N., Kumar, A., Ahmad, T., Aspect based sentiment oriented summarization of hotel reviews. Proc. Comput. Sci., 115, 563–571, Jan. 2017.

      10. Yang, C., Yu, X., Liu, Y., Nie, Y., Wang, Y., Collaborative filtering with weighted opinion aspects. Neurocomputing, 210, 185–196, Oct. 2016.

      11. Dong, R., O’Mahony, M.P., Schaal, M., McCarthy, K., Smyth, B., Sentimental product recommendation, in: Proc. 7th ACM Conf. Recommender Syst, pp. 411–414, 2013.

      12. Wang, F., Pan, W., Chen, L., Recommendation for new users with partial preferences by integrating product reviews with static specications, in: Proc. Int. Conf. Modeling, Adaptation, Pers., pp. 281–288, 2013.

      13. Musat, C.C., Liang, Y., Faltings, B., Recommendation using textual opinions, in: Proc. Int. Joint Conf. Artif. Intell., pp. 2684–2690, 2013.

      14. Jamroonsilp, S. and Prompoon, N., Analyzing software reviews for software quality-based ranking, in: Proc.10th Int. Conf. Elect. Eng./Electron., Comput., Telecommun. Inf. Technol. (ECTI-CON), May 2013, pp. 1–6.

15. Zhang, Y., Liu, R., Li, A., A novel approach to recommender system based on aspect-level sentiment analysis, in: Proc. 4th Nat. Conf. Electr., Electron. Comput. Eng. (NCEECE), pp. 1453–1458, 2015.

      16. Kermani, N.R. and Alizadeh, S.H., A hybrid multi-criteria recommender system using ontology and neuro-fuzzy techniques. Electron. Commer. Res. Appl., 21, 50–64, 2017.

      17. Wang, Y., Wang, M., Xu, W., A sentiment-enhanced hybrid recommender system for movie recommendation: a big data analytics framework. Wireless Communications and Mobile Computing, 2018, 2018.

      18. Zheng, Y., Utility-based multi-criteria recommender systems. In: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, pp. 2529–2531, 2019, April.

      19. Zheng, Y., Situation-aware multi-criteria recommender system: using criteria preferences as contexts. In: Proceedings of the Symposium on Applied Computing, pp. 689–692, 2017, April.

      20. Tallapally, D., Sreepada, R. S., Patra, B. K., Babu, K. S., User preference learning in multi-criteria recommendations using stacked auto encoders. In: Proceedings of the 12th ACM Conference on Recommender Systems, pp. 475–479, 2018, September.

      21. Hassan, M. and Hamada, M., Improving prediction accuracy of multi-criteria recommender systems using adaptive genetic algorithms. In: 2017 Intelligent Systems Conference (IntelliSys), pp. 326-330, IEEE, 2017, September.

      22. Hassan, M. and Hamada, M., A neural networks approach for improving the accuracy of multi-criteria recommender systems. Appl. Sci., 7, 9, 868, 2017.

      23. Hassan, M. and Hamada, M., Performance comparison of featured neural network trained with backpropagation and delta rule techniques for movie rating prediction in multi-criteria recommender systems. Informatica, 40, 4, 2016.

      24. Zheng, Y., Criteria chains: a novel multi-criteria recommendation approach. In: Proceedings of the 22nd International Conference on Intelligent User Interfaces, pp. 29–33, 2017, March.

      25. Ryngksai, I. and Chameikho, L., Recommender Systems: Types of Filtering Techniques. Int. J. Eng. Res. Technol., Gujarat, 3, 2278-0181, 251–254, 2014.

      26. Lakshmi, S.S. and Lakshmi, T.A., Recommendation Systems: Issues and challenges. (IJCSIT) Int. J. Comput. Sci. Inf. Technol., 5, 4, 5771–5772, 2014.

      27. Sharma, L. and Gera, A., A Survey of Recommendation System: Research Challenges. Int. J. Eng. Trends Technol. (IJETT), 4, 5, 1989–1992, 2013.

      28. Khusro, S., Ali, Z., Ullah, I., Recommender systems: issues, challenges, and research opportunities. In: Information Science and Applications (ICISA) 2016, pp. 1179–1189, Springer, Singapore, 2016.

      29. Maan, T., Gupta, S., Mishra, A., A Survey On Recommendation System. International Conference on recent innovations in management, Engineering, Science and technology (RIMEST2018), pp. 543–549, 2018.

30. Mahmoud, H., Hegazy, A., Khafagy, M.H., An approach for big data security based on Hadoop distributed file system. 2018 International Conference on Innovative Trends in Computer Engineering (ITCE), Aswan, pp. 109–114, 2018.

      31. Mohamed, M.H., Khafagy, M.H., Ibrahim, M.H., Recommender systems challenges and solutions survey. In: 2019 International Conference on Innovative Trends in Computer Engineering (ITCE), pp. 149-155, IEEE, 2019, February.

      32. Sahoo, A.K., Pradhan, C., Bhattacharyya, S., Privacy towards GIS Based Intelligent Tourism Recommender System in Big Data Analytics, in: Hybrid Computational Intelligence: Research and Applications, p. 81, 2019.

      33. Mallik, S. and Sahoo, A.K., A Comparison Study of Different Privacy Preserving Techniques in Collaborative Filtering Based Recommender System, in: Computational Intelligence in Data Mining, pp. 193–203, Springer, Singapore, 2020.

      34. Sahoo, A.K. and Pradhan, C., Accuracy-Assured Privacy-Preserving Recommender System Using Hybrid-Based Deep Learning Method, in: Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries, pp. 101–120, 2020.

      1 *Corresponding author: [email protected]

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