According to the methods of determining experts’ weights in group decision-making, the existing methods take
into account the consistency of experts’ collating vectors, but it is lack of the measure of its information similarity. So it
may occur that although the collating vector is similar to the group consensus, information uncertainty is great of a certain
expert. However, it is given the same weight to the other experts. For this, a method for deriving experts’ weights based on
entropy and cluster analysis is proposed, in which the collating vectors of all experts are classified with information similarity
coefficient, and the experts’ weights are determined according to the result of classification and entropy of collating vectors.
Finally, a numerical example shows that the method is effective and feasible.