'Norwegian University of Science and Technology (NTNU) Library'
Abstract
A reputation system computes and publishes reputation scores regarding any kind of
entity (e.g. services or goods) within a community. Since the explosion of Internet the
quantity of opinions regarding a particular item has increased dramatically, so the
relevance of reputation systems is greater than ever. Nevertheless, experience shows
that information held in a reputation centre is not fully reliable. The first challenge is to
evaluate the trustfulness of the information. Secondly, a user who is looking for advice
would prefer to give more importance to the opinions from people with a similar
profile (age, gender, etc.) in order to get a customized advice.
This work describes a framework that combines these two challenges in a single
model. A user who is looking for advice will get a customized score for an entity based
on how other users have reviewed this particular entity. In addition, the system
considers the reputation of the reviewers and matches the similarity of each reviewer
with the user looking for advice.
The tool used to develop this model is subjective logic, a kind of probabilistic logic that
allows expressing uncertainty in absence of explicit belief. Finally, we test the model
with some invented scenarios to validate it.Outgoin
