Reputation Measurement and Malicious Feedback Rating Prevention in Web Service Recommendation Systems
|Name||Reputation Measurement and Malicious Feedback Rating Prevention in Web Service Recommendation Systems|
Reputation of web services is a widely-employed metric that determines whether the service should be recommended to a user. service reputation mostly calculate from the user feedback. some factor like malicious also effect on that here first we calculate the malicious score with help of the control chart then n we reduce the effect of subjective user feedback preferences employing the Pearson Correlation Coefficient. Moreover, in order to defend malicious feedback ratings, we propose a malicious feedback rating prevention scheme employing Bloom filtering to enhance the recommendation performance. Extensive experiments are conducted by employing a real feedback rating data set with 1.5 million web service invocation records.
|ieee paper year||2015|