Chinese Journal of Intelligent Science and Technology ›› 2019, Vol. 1 ›› Issue (4): 421-426.doi: 10.11959/j.issn.2096-6652.201947

• Regular Papers • Previous Articles    

Personalized recommendation algorithm based on user behavior analysis

Jun JIA1,Bin ZHANG1,Zhiyuan LI1,Wei WEI1,Hao WEI2()   

  1. 1 Qingdao Haier (Jiaozhou) Air Conditioner Co.,Ltd.,Qingdao 266000,China
    2 School of Computer Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China
  • Revised:2019-11-22 Online:2019-12-20 Published:2020-02-29
  • Supported by:
    National Key Research and Development Project(2017YFE0101600)

Abstract:

With the development of business intelligence system and data mining technology,user behavior data has an important impact on enterprise decision-making.For the network e-commerce platform,the results of these data analysis can be used to push items of interest to specific users,which can enhance the user experience and the business value of the platform.A personalized recommendation algorithm based on user behavior analysis was proposed,which transforms user behavior information into user rating matrix,and an improved regularized nonnegative matrix decomposition algorithm was also proposed,which adds bias information to the original regularized nonnegative matrix decomposition.This algorithm can fully mine the user behavior information such as click,purchase,browse,collect,etc.,and actively push the items of interest to the users.The experimental results verify the effectiveness and efficiency of the algorithm.

Key words: behavior analysis, nonnegative matrix decomposition

CLC Number: 

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