A Trust-Based Prediction Approach for Recommendation System

  • Peng Wang
  • Haiping HuangEmail author
  • Jie Zhu
  • Lingtao Qi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10975)


The recommendation system has been widely used in e-commerce, but still suffers from data sparsity and cold-start problems. This paper combines the user trust relationship with the collaborative filtering recommendation system and puts forward the recommendation approach based on trust delivery (TDR), in order to solve the above two problems. Through calculating the quantifying trust values between users, the prediction score of an unrated item can be figured out to achieve effective recommendation. Compared with other recommendation algorithms, TDR achieves better performance on standard Mean Absolute Error (MAE) and Coverage.


Recommendation systems Trust relationship Collaborative filter 



This work was supported by the National Natural Science Foundation of P. R. China (No. 61672297), the Key Research and Development Program of Jiangsu Province (Social Development Program, No. BE2017742).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Nanjing University of Posts and TelecommunicationsNanjingChina

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