计算机科学 ›› 2017, Vol. 44 ›› Issue (2): 235-238.doi: 10.11896/j.issn.1002-137X.2017.02.038
罗晓东
LUO Xiao-dong
摘要： 移动用户偏好的动态分析由于引入了上下文数据,使得原有的用户-项目二维矩阵将扩展为用户-项目-上下文的三维矩阵。根据多维矩阵中低秩分解理论,可以简化数据的分析,但是其移动用户偏好动态分析的自学习方法没有充分利用多维矩阵的低秩分解性质。针对此问题,提出了基于多维度上下文的张量低秩分解的自学习方法,此方法基于张量的平行因子分解性质,加快了算法的收敛速度,降低了数据分析的复杂度。仿真结果验证了算法在移动用户偏好估计精度方面的有效性。
| [1] NIARAKI A S,KIM K.Ontology based personalized route planning system using a multi-criteria decision making approach[J].Expert Systems with Applications,2009,36(2):2250-2259. [2] DU C J,SUN D W.Learning techniques used in computer vision for food quality evaluation:a review[J].Journal of food engineering,2006,2(1):39-55. [3] LUO X,LV Y,LI R,et al.Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy Neural Networks for Cloud Services[J].IEEE Access,2015,3:2260-2269. [4] GHOBADI S.What drives knowledge sharing in software deve-lopment teams:A literature review and classification framework[J].Information & Management,2015,2(1):82-97. [5] CANUTO C,SIMONCINI V,VERANI M.Contraction and optimality properties of an adaptive Legendre-Galerkin method:the multi-dimensional case[J].Journal of Scientific Computing,2015,3(3):769-798. [6] CEPEDA-GOMEZ R,MICHIELS W.Some special cases in the stability analysis of multi-dimensional time-delay systems using the matrix Lambert W function[J].Automatica,2015,3:339-345. [7] FORSYTHE P,JUPP J,SAWHEY A.Building informationmodelling in tertiary construction project management education:A programme-wide implementation strategy[J].Journal for Education in the Built Environment,2013,8(1):16-34. [8] RODRIGUEZ-SANCHEZ M C,MARTINEZ-ROMO J,BOR-ROMEO S,et al.GAT:Platform for automatic context-aware mobile services for m-tourism[J].Expert Systems with Applications,2013,40(10):4154-4163. [9] MEHROTRA A,HENDLEY R,MUSOLESI M.PrefMiner:Mining User’s Preferences for Intelligent Mobile Notification Management[C]∥ The 2016 ACM International Joint Confe-rence on Pervasive and Ubiquitous Computing(UbiComp 2016).2016:1223-1234. [10] CHOU C K,LIN C C,CHEN M S.Context-aware daily activity summarization with adaptive transmission[C]∥Proceedings of the 31st Annual ACM Symposium on Applied Computing.ACM,2016:560-565. [11] GARZA P,QUINTARELLI E,RABOSIO E,et al.Reducing Big Data by Means of Context-Aware Tailoring[M]∥New Trends in Databased and Information Systems.Springer International Publishing,2016:115-127. [12] OH K J,KIM Z,OH H,et al.Travel intention-based attraction network for recommending travel destinations[C]∥2016 International Conference on Big Data and Smart Computing (BigComp).IEEE,2016:277-280. [13] ZHANG J W,YANG Z.Collaborative Filtering Recommendation Algorithm Based on Improved User Clustering[J].Compu-ter Science,2014,1(12):176-178.(in Chinese) 张峻玮,杨洲.一种基于改进的层次聚类的协同过滤用户推荐算法研究[J].计算机科学:2014,41(12):176-178. [14] YU X S,SHAN H.Research on Personalized RecommedationModel Based on Network Users’ Information Behavior[J].Journal of Chongqing Institute Technology,2013,7(1):47-50.(in Chinese) 余肖生,孙珊.基于网络用户信息行为的个性化推荐模型[J].重庆理工大学这报(自然科学版),2013,27(1):47-50. |
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