Big datatransaction is a key point of promoting data circulation and data value.It is important for building efficient and robust trading platform to optimize process of big datatransaction.Big data transaction is a typical complex process model

which makes the traditional model repair method not able to effectively discoverand reduce the deviation between process execution and process rules.This paper proposes an approach of repairing big datatransaction model based on deviation reduction.With the help of the reachable marking graph

the approach discovers the deviation between the event log and the process model found

reduces the deviation between the event log and the model

and gets the repaired model based on the effective deviation.At the end of this paper

the proposed approach is used in the Tianyuan big data platform to verify the effectiveness.By comparison experiments of those repair methods based on model alignment and the iteration of the effect of repairing is evaluated from the aspects of fitness

precision

simplicity and time complexity.The evaluation shows that the proposed approach has an advantage over existing methods.