Improving Non Personalized Recommendations using a Non-Linear Weighted Mean
AbstractRecommender Systems have become an important part of our day to day life. The goal of any recommendation system is to present users with a relevant set of items which would interest them. This paper showcases a new technique and implements a non-personalized recommender system using the proposed technique. It is shown how the modification can be used to improve the recommendation as compared to existing algorithms. The comparison is done with the widespread method of average ratings and conclusions are drawn based on these tests.
 Davidson, J., Liebald, B., Liu, J., Nandy, P., Vleet, T. V., Gargi, U., Sampath, D. (2010). The YouTube video recommendation system. Proceedings of the fourth ACM conference on Recommender systems. Barcelona.
 Howe, M. (2003). Pandora's Music Recommender.
 Osinski, l. S., J.S, & Weiss, D. (2004). Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition. In W. S. Kłopotek M.A., Intelligent Information Processing and Web Mining. Advances in Soft Computing (Vol. 25). Berlin: Springer.
 Jajoo, P. (2008). Document Clustering. Thesis, Indian Institute of Technology , Department of Computer Science & Engineering , Kharagpur.
 Billsus, D., & Pazzani, M. J. (2007). Content-based Recommendation Systems. In P. Brusilovsky, A. Kobsa, & W. Nejdl, The Adaptive Web. Lecture Notes in Computer Science (Vol. 4321, pp. 325-341). Berlin: Springer.
 Campos, L. d. (2010). Combining content-based and collaborative recommendations: A hybrid approach based on Bayesian networks. International Journal of Approximate Reasoning, 785-799.
 Liu, J., P.D, & Pederson, E. R. (2010). Personalized News Recommendation Based on Click Behavior. Proceedings of the 15th international conference on Intelligent user interfaces. Hong Kong.
 Sarwar, B., G.K, Konstan, J., & Riedl, J. (2001). Item-Based Collaborative Filtering Recommendation Algorithms. Proceedings of the 10th international conference on World Wide Web, (pp. 285-295). Hong Kong.
 Bogers, T., & Bosch, A. v. (2009, January). Collaborative and Content-based Filtering for Item Recommendation on Social Bookmarking Websites. Proceedings of the ACM RecSys '09 workshop on Recommender Systems and the Social Web.
 Poriya, A., N.P, Bhagat, T., & Sharma, R. (2014). Non-Personalized Recommender Systems and User- based Collaborative Recommender Systems. International Journal of Applied Information Systems .
 Cremonski, P., Koren, Y., & Turrin, R. (2010). Performance of Recommender Algorithms on Top-N Recommendation Tasks. Proceeding RecSys '10 Proceedings of the fourth ACM conference on Recommender systems, (pp. 39-46).
 Koren, Y. (2008). Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model. Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, (pp. 426-434).
 Miller, E. (2012). Bayesian Average Ratings. Retrieved from evanmiller.com: http://www.evanmiller.com/bayesian-average-ratings.html
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