JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (1): 89-94.doi: 10.6040/j.issn.1671-9352.1.2015.106

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Trust-aware product recommendation based on factorization machine

GAO Xiao-bo1, FANG Xian-mei1,2*, LI Shi-jun2   

  1. 1. School of Computer and Information Engineering, Hechi University, Yizhou 546300, Guangxi, China;
    2. Computer School, Wuhan University, Wuhan 430079, Hubei, China
  • Received:2015-08-06 Online:2016-01-16 Published:2016-11-29

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Abstract: The personalized recommender system suffers from sparse data and slow recommendation speed. A score prediction model based on Factorization Machine(FM)was proposed. The FM model utilizes users access history, identifies user-interested contents based on their scoring records and integrates trusts among different users. FM has a linear time complexity and excellent learning capability for sparse data, so it can quickly recommend. The results showed that the proposed FM model based on product recommendation approach was significantly more accurate than the traditional methods.

Key words: e-commerce, factorization machine, trust, product recommendation

CLC Number: 

  • TP391
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