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Chen, \u201cAdaptive personalized recommendation based on adaptive learning,\u201d Neurocomputing, vol.74, no.11, pp.1848-1858, 2011.","DOI":"10.1016\/j.neucom.2010.07.034"},{"key":"5","unstructured":"[5] T. Zhang and V.S. Iyengar, \u201cRecommender systems using linear classifiers,\u201d J. Machine Learning Research 2, pp.313-334, 2002."},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] M.S. Reddy and T. Adilakshmi, \u201cMusic recommendation system based on matrix factorization technique-SVD,\u201d In Computer Communication and Informatics (ICCCI), 2014 International Conference on, IEEE, pp.1-6, 2014.","DOI":"10.1109\/ICCCI.2014.6921744"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] Y. Seroussi, F. Bohnert, and I. Zukerman, \u201cPersonalised rating prediction for new users using latent factor models,\u201d Proc. 22nd ACM Conference on Hypertext and hypermedia, New York, NY, USA, pp.47-56, 2011.","DOI":"10.1145\/1995966.1995976"},{"key":"8","unstructured":"[8] W. Hong, L. Li, and T. Li, \u201cProduct recommendation with temporal dynamics,\u201d Expert Systems with Applications, vol.39, no.16, pp.12398-12406, 2012."},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] W. Hong, L. Li, and T. Li, \u201cProduct recommendation with temporal dynamics,\u201d Expert Systems with Applications, vol.39, no.16, pp.12398-12406, 2012.","DOI":"10.1016\/j.eswa.2012.04.082"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] J. Gu, M. Zhu, and L. Jiang, \u201cHousing price forecasting based on genetic algorithm and support vector machine,\u201d Expert Systems with Applications, vol.38, no.4, pp.3383-3386, 2011.","DOI":"10.1016\/j.eswa.2010.08.123"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] J. Kennedy and R. Eberhart, \u201cParticle swarm optimization,\u201d Encyclopedia of Machine Learning, pp.760-766, 2010.","DOI":"10.1007\/978-0-387-30164-8_630"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] F. Luo, J. Zhao, J. Qiu, J. Foster, Y. Peng, and Z. Dong, \u201cAssessing the transmission expansion cost with distributed generation: an Australia case study,\u201d IEEE Transactions on Smart Grid, vol.5, no.4, pp.1892-1904, 2014.","DOI":"10.1109\/TSG.2014.2314451"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Y. Zheng, Z.Y. Dong, F.J. Luo, K. Meng, J. Qiu, and K.P. Wong, \u201cOptimal allocation of energy storage system for risk mitigation of DISCOs with high renewable penetrations,\u201d IEEE Trans. Power Syst., vol.29, no.1, pp.212-220, 2014.","DOI":"10.1109\/TPWRS.2013.2278850"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] Y. Shi and R.C. Eberhart, \u201cEmpirical study of particle swarm optimization,\u201d Proc. 1999 Congress on Evolutionary Computation, vol.3, pp.101-106, 1999.","DOI":"10.1109\/CEC.1999.785511"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] A. Ratnaweera, S.K. Halgamuge, and H.C. Watson, \u201cSelf-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients,\u201d Evolutionary Computation, IEEE Transactions on, vol.8, no.3, pp.240-255, 2004.","DOI":"10.1109\/TEVC.2004.826071"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] J.C. Bansal, P.K. Singh, M. Saraswat, A. Verma, S.S. Jadon, and A. Abraham, \u201cInertia weight strategies in particle swarm optimization,\u201d In Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on. IEEE, pp.633-640, 2011.","DOI":"10.1109\/NaBIC.2011.6089659"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] M.A. Arasomwan and A.O. Adewumi, \u201cOn the performance of linear decreasing inertia weight particle swarm optimization for global optimization,\u201d The Scientific World Journal, vol.2013, pp.1-12, 2013.","DOI":"10.1155\/2013\/860289"},{"key":"18","unstructured":"[18] MovieLens Datasets. http:\/\/grouplens.org\/datasets\/movielens\/"},{"key":"19","unstructured":"[19] I.H. Witten and E. Frank, \u201cData mining: Practical machine learning tools and techniques,\u201d Morgan Kaufmann, 2005. http:\/\/prdownloads.sourceforge.net\/weka\/datasets-UCI.jar"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] M.A. Arasomwan and A.O. 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