Improving the Enhanced Recommended System Using Bayesian Approximation Method and Normalized Discounted Cumulative Gain

Reputation is an effective source for measuring trust. In e-learning environments, co-learners trust relationships play a vital role to establish collaborative activities. Ratings/ranking provides an efficient and effective way to build trust relationship among faculties and students in e-learning environment. Content driven reputation systems is based on the feedback provided by analysis of all interactions whereas user driven reputation systems is based only on the feed-back or ratings provided by the users. Z-score is the popular ranking calculating method which compares sample with population or 2 samples, paired or unpaired. ANOVA/F tests are similar to Z-score but use variances instead of means and can be applied to more than 2 groups and other more complex scenarios. This paper includes the online rating calculation method, Bayesian Approximation, for reputation management and Normalized Discounted Cumulative Gain as a metric for measuring ranking correctness.