Modeling for Comment Trust Recommendation Based on Collaborative Filtering
- Xinkao Liao, Lisheng Wang, Xiaojian Liu, Xiaojie Xu
- Corresponding Author
- Xinkao Liao
Available Online July 2015.
- https://doi.org/10.2991/lemcs-15.2015.32How to use a DOI?
- E-commerce; Collaborative Filtering; PeopleRank; Trust Recommendation; Cold Startup Problem;
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/lemcs-15.2015.32 DO - https://doi.org/10.2991/lemcs-15.2015.32 ID - Liao2015/07 ER -