Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 46-50.doi: 10.11896/j.issn.1002-137X.2017.11A.008

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Ordering Recommender Algorithm Based on Consumers’ Behavior

DING Dang, ZHANG Zhi-fei, MIAO Duo-qian and CHEN Yue-feng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: With the development of e-commerce,most of the existing catering management system lags consumers and managers’ need.An effective approach is to apply recommendation systems to catering management,and to provide ordering recommendations according to consumers’ behavior data.As for cold start problems that may arise in the recommending process,the ordering recommender system based on consumers’ behavior was proposed,containing three re-commendation engines,which are frequency statistics,association rules and Markov chain .Experiments on ordering data of real restaurants achieve a satisfactory result,and get a weight combination of three recommendation engine:(0.2167,0.5167,0.2666),and the best recommending length under that weight:3.

Key words: Data mining,Recommendation system,Association rules,Markov chain,Catering management

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