Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2009
Abstract
This paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied Trust Antecedent framework in management science. To apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. The advantage of this approach is that features relevant to trust can be systematically derived so as to achieve good prediction accuracy. Through a series of experiments on real data from Epinions, we show that even a simple model using the derived features yields good accuracy and outperforms MoleTrust, a trust propagation based model. SVM classifiers using these features also show improvements.
Keywords
Trust prediction, Trust ranking, Trust antecedent framework
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
IEEE International Conference on Data Mining
First Page
896
Last Page
901
ISBN
9780769538952
Identifier
10.1109/ICDM.2009.115
Publisher
IEEE ICDM
City or Country
Miami, Florida, Dec 6-9
Citation
Viet-An Nguyen, Ee-Peng Lim, Jing Jiang, Aixin Sun. 2009. "To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework." Ninth IEEE International Conference on Data Mining, 896-901.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.ieeecomputersociety.org/10.1109/ICDM.2009.115
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons