[Agarwal, N., Haque, E., Liu, H., & Parsons, L. (2005). Research paper recommender systems: A subspace clustering approach. In Advances in Web-Age Information Management (pp. 475–491). Springer.10.1007/11563952_42]Search in Google Scholar
[Anand, S. S., & Mobasher, B. (2003). Intelligent techniques for web personalization. In Proceedings of the 2003 International Conference on Intelligent Techniques for Web Personalization (pp. 1–36). Springer-Verlag.]Search in Google Scholar
[Bridge, D., & Kelleher, J. (2002). Experiments in sparsity reduction: Using clustering in collaborative recommenders. In Artificial Intelligence and Cognitive Science (pp. 144–149). Springer.10.1007/3-540-45750-X_18]Search in Google Scholar
[Cremonesi, P., Donatacci, A., Garzotto, F., & Turrin, R. (2012). Decision-Making in Recommender Systems: The Role of User's Goals and Bounded Resources. In 6th ACM Conference on Recommender Systems (pp. 1–7).]Search in Google Scholar
[Gavalas, K. M. D. (2011). A web-based pervasive recommendation system for mobile tourist guides. In Personal and Ubiquitous Computing (Vol. 15, pp. 759–770). Springer-Verlag.10.1007/s00779-011-0389-x]Search in Google Scholar
[Haruechaiyasak, C., Tipnoe, C., Kongyoung, S., Damrongrat, C., & Angkawattanawit, N. (2005). A dynamic framework for maintaining customer profiles in e-commerce recommender systems. In IEEE International Conference on e-Technology, e-Commerce and e-Service, (pp. 768–771).10.1109/EEE.2005.8]Search in Google Scholar
[Jain, A. K., Murty, M. N., & Flynn, P. J. (1999) Data clustering: a review. ACM Computing Surveys, 31(3), 264–323.10.1145/331499.331504]Search in Google Scholar
[Jannach, D., Zanker, M., Felfernig, A., & Friedrich, G. (2010). Recommender systems: an introduction, Cambridge University Press.10.1017/CBO9780511763113]Search in Google Scholar
[Kantor, P. B., Ricci, F., Rokach, L., & Shapira, B. (2011). Recommender systems handbook. Springer.]Search in Google Scholar
[Kim, Y. S., T.H. (2005). An Effective Recommendation Algorithm for Clustering-Based Recommender Systems. In Lecture Notes in Artificial Intelligence (Vol. 3809, p. 1150–1153). Springer-Verlag.10.1007/11589990_159]Search in Google Scholar
[Kużelewska, U. (2013). Advantages of Information Granulation in Clustering Algorithms. In Agents and Artificial Intelligence (pp. 131–145). Springer.10.1007/978-3-642-29966-7_9]Search in Google Scholar
[Li, L., Wang, D.-D., Zhu, S.-Z., & Li, T. (2011). Personalized news recommendation: a review and an experimental investigation. Journal of Computer Science and Technology, 26(5), 754–766.10.1007/s11390-011-0175-2]Search in Google Scholar
[Mahmood, T., & Ricci, F. (2009). Improving recommender systems with adaptive conversational strategies. In Proceedings of the 20th ACM Conference on Hypertext and Hypermedia (pp. 73–82).10.1145/1557914.1557930]Search in Google Scholar
[Malak, A.-H., Yan, L. H., & Jie, L. (2011). Personalized e-Government Services: Tourism Recommender System Framework. In Lecture Notes in Business Information Processing, (Vol. 75, p. 173–187). Springer.]Search in Google Scholar
[Moghaddam, S. G., & Selamat, A. (2011). A scalable collaborative recommender algorithm based on user density-based clustering. In 3rd International Conference on Data Mining and Intelligent Information Technology Applications (ICMiA) (pp. 246–249).]Search in Google Scholar
[MovieLens 100k Data Set. (n.d). Retrieved 01.02.2013, from http://www.grouplens.org/node/73.]Search in Google Scholar
[Pitsilis, G. e. a. (2011). Clustering Recommenders in Collaborative Filtering Using Explicit Trust Information. In Trust Management V (Vol. 358, p. 82–97). Springer.10.1007/978-3-642-22200-9_9]Search in Google Scholar
[Rongfei, J., Maozhong, J., & Chao, L. (2010). A new clustering method for collaborative filtering. In International Conference on Networking and Information Technology (pp. 488–492).10.1109/ICNIT.2010.5508465]Search in Google Scholar
[Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International Conference on World Wide Web (pp. 285–295).10.1145/371920.372071]Search in Google Scholar
[Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2002). Recommender systems for large-scale e-commerce: Scalable neighborhood formation using clustering. In Proceedings of the 5th International Conference on Computer and Information Technology (Vol. 1).]Search in Google Scholar
[Schiaffino, A. A., S. (2009). Building an expert travel agent as a software agent. In Expert Systems with Applications (Vol. 36, pp. 1291–1299). Elsevier.10.1016/j.eswa.2007.11.032]Search in Google Scholar