An outlier expert detection model for group decision making based on support vector domain description

Quality of organization decision making can be increased greatly by group decision, and more and more managers begin pay attention to this method. But there are still some problems existed in group decision, such as in some case, experts´ ability, attitude and confidence will greatly affect decision result, and how to find abnormal expert and reduce his decision weight or dismiss him from the decision group is very important for increasing decision quality. For the reason above, this paper tries to find an effective method for avoiding abnormal experts´ negative effect. And build a model for recognize abnormal experts based on support vector domain description, and the model take the experts´ decision activities as input and the model will automatically find out the outlier expert according his abnormal decision activities.