Online rating system credibility People depend on online rating systems for deciding their purchases. The problem of the online rating system is the credibility of the ratings. Sometimes feedback rating really reflect customers opinion about products but sometimes not. Salhuldin Alqarghuli: Alqarghs@email.sc.edu

Apply all proposed solutions together Provenance-Aware: We need contextual information about the ratings. For example: Educational level of each user. The average grade of each student. Define a weight function that depends on the contextual attributes. Salhuldin Alqarghuli: Alqarghs@email.sc.edu

Multi-dimensional Reputation Example: the eBay feedback system and students feedback in educational systems. The correlation among ratings can help a reputation system to accurately assess the quality of ratings. We obtain k trustworthiness ranks for each user, we aggregate these trustworthiness ranks using a simple average to obtain the final users’ trustworthiness. Salhuldin Alqarghuli: Alqarghs@email.sc.edu

Salhuldin Alqarghuli: Alqarghs@email.sc.edu Collusion Detection Users may collaboratively promote or demote a product. Collaborative unfair rating collusion is more damaging than individual unfair rating. We can depend on several indicators for identifying collusion: Similar rating scores for similar products. Cast ratings in a short period of time. Salhuldin Alqarghuli: Alqarghs@email.sc.edu