Abstract
More and more business requirements are crossing organizational boundaries. There comes the cross-organization business process management, and its modeling is a complicated task. Mining a cross-organization business process aims to discover its model from a set of distributed event logs. Unfortunately, traditional process mining approaches totally neglect the privacy-preservation issue, which means the privacy of both event log and business process model. In this paper, a privacy-preservation cross-organization business process mining framework is proposed to handle its privacy issues. It includes three steps: (1) each organization discovers its private and public business process models from its event logs; (2) the trusted third-party midware takes the public process models as input and generates cooperative public process model fragments of each organization; and (3) each organization combines its private business process model with its relevant public fragments to obtain the organization-specific cross-organization cooperative business process model. To illustrate the applicability of the proposed approach, a multi-modal cross-organization transportation case is used for its validation and comparison with other methods.