Roundtable Gossip Algorithm: A Novel Sparse Trust Mining Method for Large-Scale Recommendation Systems

  • Mengdi Liu
  • Guangquan XuEmail author
  • Jun Zhang
  • Rajan Shankaran
  • Gang Luo
  • Xi Zheng
  • Zonghua Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11337)


Cold Start (CS) and sparse evaluation problems dramatically degrade recommendation performance in large-scale recommendation systems such as Taobao and eBay. We name this degradation as the sparse trust problem, which will cause the decrease of the recommendation accuracy rate. To address this problem we propose a novel sparse trust mining method, which is based on the Roundtable Gossip Algorithm (RGA). First, we define the relevant representation of sparse trust, which provides a research idea to solve the problem of sparse evidence in the large-scale recommendation system. Based on which the RGA is proposed for mining latent sparse trust relationships between entities in large-scale recommendation systems. Second, we propose an efficient and simple anti-sparsification method, which overcomes the disadvantages of random trust relationship propagation and Grade Inflation caused by different users have different standard for item rating. Finally, the experimental results show that our method can effectively mine new trust relationships and mitigate the sparse trust problem.


Sparse trust relationship Anti-sparsification Recommendation system 



This work has been partially sponsored by the National Science Foundation of China (No. 61572355, U1736115), the Tianjin Research Program of Application Foundation and Advanced Technology (No. 15JCYBJC15700), and the Fundamental Research of Xinjiang Corps (No. 2016AC015).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Tianjin Key Laboratory of Advanced Networking (TANK), School of Computer Science and TechnologyTianjin UniversityTianjinChina
  2. 2.School of Software and Electrical EngineeringSwinburne University of TechnologyMelbourneAustralia
  3. 3.Department of ComputingMacquarie UniversitySydneyAustralia
  4. 4.IMT Lille DouaiDouaiFrance

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