|
Abstract
|
Trust network can be useful tool for identification
of the trustful sources of information in a social web application.
Despite the usefulness of a trust network, it is usually sparse as
users are generally reluctant to express the trust relationships.
Therefore, one approach to make the trust network denser is to
identify the potential trust relationships between users and
recommend the reliable and trustful participant to users. The
main contribution of this research is the examination of the
performance of Locally Linear Neuro Fuzzy (LLNF) model in the
trust prediction context. Therefore, LLNF was compared with
two classification techniques including ANFIS and C4.5 decision
tree. To conduct experiments, data of Epinions network were
used. The results of experiments demonstrate that LLNF
achieves the highest performance in terms of area under ROC
(AUC). In addition, LLNF follows closely C4.5 decision tree
regarding F-measure. LLNF can be a good candidate for trust
relationships prediction.
|