Modeling for Comment Trust Recommendation Based on Collaborative Filtering

DOI

10.2991/lemcs-15.2015.32How to use a DOI?

Keywords

E-commerce; Collaborative Filtering; PeopleRank; Trust Recommendation; Cold Startup Problem;

Abstract

Asymmetry in the parties of the transaction leads to uncertainty in the transaction. Trust problem has been one of the bottlenecks restricting the development of e-commerce. For e-commerce product review issues, comment trust recommendation model was proposed based on comment credibility degree and user similarity, which combined with social networking trust mechanism and collaborative filtering to offer users with a more personalized trust recommendations. The experimental results demonstrate that the model can effectively improve the recommendation accuracy and solve cold startup problems in collaborative filtering.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xinkao Liao
AU  - Lisheng Wang
AU  - Xiaojian Liu
AU  - Xiaojie Xu
PY  - 2015/07
DA  - 2015/07
TI  - Modeling for Comment Trust Recommendation Based on Collaborative Filtering
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 162
EP  - 166
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.32
DO  - 10.2991/lemcs-15.2015.32
ID  - Liao2015/07
ER  -