A Pre-evaluating Set based Bias-tuned Reputation Evaluation Method for Trust Establishment in Grid

For the scale, openness and sharing of grid environment, how to establish a reliable trust relationship between unknown entities more and more challenges grid systems. With wide application in electronic commerce and online communities, reputation mechanism emerges as a promising solution, where a scientific reputation evaluation method is crucial. Yet, most methods currently available do not consider grid´s distinct characteristics such as the sparseness of ratings and strangeness of entities, which are not feasible to grid. In this paper, we propose a pre-evaluating set based method for reputation evaluation in grid. The introduction of the pre-evaluating set is to overcome the sparseness and strangeness mentioned above. With this set, we can effectively tune a rater´s bias to cater to the current evaluator´s criteria and reasonably weight a rater´s rating in aggregation. For bias-tuning, we flexibly turn this into an interpolation problem and conveniently solve it in Matlab. For the final aggregation, we introduce the notion of criteria coherent degree for weight calculation