Abstract: In view of the problems of the coexistence of multi-source information， incomplete information， and non-independent evaluation questions of evaluation information， an integrated framework for multi-relational blended information and an information aggregation method are proposed. Firstly， the blended uncertain information is classified and integrated， the correlations are explored among information(sub)streams， and the integrated framework for multi-relational blended uncertain information is constructed. Secondly， the blended uncertain information is transformed into random numbers by simulation iterations to fully tap the value of information. Then， through the relationship graph of information(sub)flows， the information weight of information(sub)flows is solved by using the analytic network process(ANP). Finally， by comparing the results of each simulation iteration of the evaluated object， the pairwise priority matrix is obtained， and the probability ranking reflecting the probability characteristics is obtained by the regression tree method. The fusion of blended incomplete information and multi-relational information are explored by constructing the integrated framework for multi-relational blended uncertain information. The requirements for data integrity in the evaluation process are reduced， and information overlapping and information redundancy are considered. The relative conclusion is more explanatory for the practical problems.

Key words: integrated assessment; integrated framework for multi-relational blended uncertain information; ANP; stochastic simulation; the most likely ranking