A Trust Rating Model of Recommendation in Grid

The trust rating of recommendation for one entity greatly depends on the trust in the recommenders´ ability to provide recommendations. To prevent the cahoots, cheating and fluctuant fraudulence in recommendation, we studied the characteristics of the two classes of true and false recommendation. On the basis of the analysis of the feature set, a distinguishing model is created to effectively identify the baleful entities that provide false recommendations in grid system, thus increasing the veracity of trust rating. The model checking shows that this scheme is of high feasibility.