Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

Modeling for Comment Trust Recommendation Based on Collaborative Filtering

Authors
Xinkao Liao, Lisheng Wang, Xiaojian Liu, Xiaojie Xu
Corresponding Author
Xinkao Liao
Available Online July 2015.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-6252-102-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/lemcs-15.2015.32How to use a DOI?
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  -