[1] Albadvi A., Chaharsooghi K., and Esfahanipour A (2007) "Decision making in stock trading: An application of PROMETHEE", European Journal of Operational Research, 673-683.
[2] Asosheh, A., Bagherpour, S. Yahyapour, N. (2008). "Extended acceptance models for recommender system adaption, case of retail and banking service in Iran", WSEAS transactions on business and economics, 5(5): 189-200.
[3] Bahrinizadeh, M., Esmailpour, M., Kaboutari, J (2017). "Evaluating and Ranking the Quality Components of E-Services Affecting Customer Satisfaction and Intent", Journal of Business Intelligence Management Studies, vol. 22, pp. 49-74.
[4] Borhani Zarandi, S., Niknafas, Mohammadi (2013). "Opinion mining in product review by using emotional vocabulary", 2nd national conference on Industrial & Systems Engineering, Islamic Azad University of Najafabad.
[5 Chao Ma ., Xun Liang (2015). "Online mining in unstructured financial information", An empirical study in bulletin news.
[6] Chen Y.-L. and Cheng L.-C (2008) "A novel collaborative filtering approach for recommending ranked items", Expert systems with applications, vol. 34, pp. 2396-2405.
[7] Cornelis C., Lu J., Guo X., and Zhang G (2007) "One-and-only item recommendation with fuzzy logic techniques", Information sciences, vol. doi:10.1016/j.ins.2007.07.001.
[8] Fasanghari M., Montazer Gh (2010), "Design and implementation of fuzzy expert system for Tehran Stock Exchange portfolio recommendation", Expert Systems with Applications, 37(9), 6138–6147,
[9] Islam M., Habib M. (2015), "A data mining approach to predict prospective business sectors for lending in Retail banking using decision tree", arXiv preprint arXiv:1504.02018.
[10] Jin, J., P. Ji and R. Gu (2016) "Identifying comparative customer requirements from product online reviews for competitor analysis." Engineering Applications of Artificial Intelligence 49: 61-73.
[11] Kangas, S. (2002) "Collaborative filtering and recommendation systems. in: VTT information technology". Espoo: VTT.
[12] Karimian, S., Karegar, M. (2012) "Quantifying the emotional tendency of Persian-language customer comments on the features of the product on the Web", 1st international conference of web research, Knowledge and Culture University.
[13] Karimi Alavije, M., Askari, S. & Parasite, S. (2015) "Intelligent Online Store: User Behavior Analysis based Recommender System", Journal of Information Technology Management. 7(2): 385-406.
[14] Kim, Y. S., Yum, B. J., Song, J. & Kim, S. M. (2005), "Development of a recommender system based on navigational and behavioral patterns of customers in e-commerce sites", Expert Systems with Applications. 28(1): 381-393.
[15] Kompan, M. & Bieliková, M. (2010), "Content-based news recommendation", International Conference on Electronic commerce and web technologies (EC-Web 2010), University of Deusto, Bilbao, 30 August - 3 September 2010.
[16] Liu, B., M. Hu and J. Cheng (2005) "Opinion observer: analyzing and comparing opinions on the Web", Proceedings of the 14th international conference on World Wide Web. Chiba, Japan, ACM: 342-351.
[17] Li Y., Lu L., and Xuefeng L (2005), "A hybrid collaborative filtering method for multiple-interests and multiplecontent recommendation in E-Commerce", Expert systems with applications, vol. 28, pp. 67-77.
[18] Marrese-Taylor, E., J. D. Velásquez and F. Bravo-Marquez (2014), "A novel deterministic approach for aspectbased opinion mining in tourism products reviews", Expert Systems with Applications 41(17): 7764-7775.
[19] Martín-Guerrero, J. D. & Lisboa, P. J. & Soria-Olivas, E. & Palomares, A. & Balaguer, E. (2007), "An approach based on the Adaptive Resonance Theory for analyzing the viability of recommender systems in a citizen Web portal", Expert Systems with Applications, 33(3): 743-753.
[20] Miles, M.B.& Hubermn, A.M. (2017), "Qualitative Data Analysis" – A Sourcebook of New Methods, California, Sage.
[21] Rouhani S., Zandvakili R., Ansari M (2018), " Design and Implementation of a Tag-oriented Recommender System Based on Deep Neural Networks", Journal of Modern Research in Decision Making. Vol. (3) 2, 155-174.
[22] Sohrabi B., Raeesi Vanani I., Zareh Mirkabad F (2016), " Designing a Recommender System for Optimizing and Managing Bank Facilities through the Utilization of Clustering and Classification Algorithms", Journal of Modern Research in Decision Making. Vol. (1) 2, 53-76.
[23] Soleimani-Roozbahani F., Rajabzadeh Ghatari A., Radfar R (2019) "Knowledge discovery from a more than a decade studies on healthcare Big Data systems: a scientometrics study", vol. 6, pages.8,
Journal of Big Data. doi:
https://doi.org/10.1186/s40537-018-0167-y
[24] Taymouri asl Y., Jokar A (2015), "Provide a model of market orientation in the Iranian banking industry using the Delphi method", Journal of Management Research in Decision Making. Vol. (19)1, 45-67.
[25] Wang, Z., Sun, L., Zhu, W., Yang, S., Li, H. & Wu, D. (2013), "Joint social and content recommendation for user-generated videos in online social network"" IEEE Transactions on Multimedia, 15(3): 698-709.
[26] Xiaoming YANG Peng TIAN Zhen ZHANG, (2019)" A Comparative Study on Several National Customer Satisfaction Indices (CSI)" Aetna School of Management,Shanghai Jiao Tong University, Shanghai, P.R.China, ,p2
[27] Yang X., Chen J., Hao P., Wang Y. J (2015), "Application of clustering for customer segmentation in private banking", Seventh International Conference on Digital Image Processing, 96311Z; doi:10.1117/12.2197182.
[28] Yin, D. & Hong, L. & Davison, B. D (2011), "Structural link analysis and prediction in microblogs", Proceedings of the 20th ACM international conference on Information and knowledge management. Glasgow, 24-28.
[29] Zahra S., Ghazanfar M. A., Khalid A., Azam M. A., Naeem U., Prugel-Bennett A. (2015), "Novel centroid selection approaches for KMeans-clustering based recommender systems", Information Sciences, 320, 156-189. doi:
[30] Zarei A (2015), "Developing a Structural Model for Customer Churn in Governmental Banks: Case of Semnan Governmental Banks", Journal of Management Research in Decision Making. Vol. (21)1, 151-176.