期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：4
页码：5318
DOI：10.15680/IJIRCCE.2016.0404237
出版社：S&S Publications
摘要：In recent years,recommendation systems have seen significant evolutionin the field of knowledge engineering.Most of the existing recommendation systems based their models on collaborative filtering approaches that make them simple to implement.However performance of most of the existing collaborative filtering-based recommendation system suffers due to the challenges such as: (a) cold start, (b) data sparseness, and (c) scalability.In this paper we proposedMobicontext, a hybrid cloud-based Bi-Objective Recommendation Framework(BORF) for mobile social networks.The mobicontextutilizes multi-objective optimization techniques to generate personalized recommendations.To address the issues pertaining to coldstart and data sparseness, the BORF performs data pre-processing by using the Hub-Average(HA) inference model.Moreover,the Weighted Sum Approach(WSA) is implemented for scalar optimization and an evolutionary algorithm(NSGA-II) is applied for vector optimization
