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Refining Reputation Systems applying Subjective Logic
Cardelus Soler, Carles
Knapskog, Svein Johan
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.
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Àrees temàtiques de la UPC::Matemàtiques i estadística::Lògica matemàtica
Web site development
Public opinion polls
Logic, Symbolic and mathematical
Information filtering systems
Artificial intelligence
Pàgines web -- Desenvolupament
Opinió pública -- Sondejos
Lògica probabilística
Informació -- Sistemes d'emmagatzematge i recuperació
Intel·ligència artificial
Universitat Politècnica de Catalunya;
Norwegian University of Science and Technology

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