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In this paper, we analyze the contextual information on cold chain logistics distribution and propose a multidimensional context-aware recommendation algorithm(MCARA). MCARA firstly carries out fuzzy clustering on contextual information in historical data set and obtains the contextual clusters. In addition, MCARA compares current user context with historical contexts to get current contextual cluster, and selects out the data with same contextual clusters from historical data set. Finally, MCARA uses the user-based collaborative filtering algorithm to perform personalized recommendations. The simulation results show that MCARA can improve the forecast accuracy of cold chain logistics distribution, with about 10% improvement over other eight approaches.<\/jats:p>","DOI":"10.3233\/jifs-169578","type":"journal-article","created":{"date-parts":[[2018,6,5]],"date-time":"2018-06-05T14:30:50Z","timestamp":1528209050000},"page":"171-185","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Multidimensional context-aware recommendation algorithm towards intelligent distribution of cold chain logistics"],"prefix":"10.1177","volume":"35","author":[{"given":"Xiang","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer and Information, Hohai University, Nanjing, China"},{"name":"Faculty of Computer and Software, Huaiyin Institute of Technology, Huaian, China"}]},{"given":"Zhijian","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Software, Huaiyin Institute of Technology, Huaian, China"}]}],"member":"179","published-online":{"date-parts":[[2018,6,5]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.11.005"},{"issue":"4","key":"e_1_3_2_3_2","first-page":"2403","article-title":"A general heuristic for vehicle routing problems","volume":"38","author":"David P.","year":"2007","unstructured":"DavidP. and StefanR., A general heuristic for vehicle routing problems, Computers & Operations Research38(4)(2007), 2403\u20132435.","journal-title":"Computers & Operations Research"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.03.030"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1287\/trsc.1030.0070"},{"issue":"3","key":"e_1_3_2_6_2","first-page":"337","article-title":"Fuzzy optimization for distribution of frozen food with imprecise times","volume":"11","author":"Brito J.","year":"2012","unstructured":"BritoJ., MartinezF.J. and MorenoJ.A., Fuzzy optimization for distribution of frozen food with imprecise times, Journal of Mathematical Modelling and Algorithms in Operations Research. 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