13. A computer readable non-transitory storage medium embodying instructions executed by a plurality of processors for updating a probabilistic process model (PPM) of a semi-structured business process, the method comprising: receiving the PPM and at least one probability distribution corresponding to a decision node of the PPM, wherein the received PPM includes all possible execution sequences of the semi-structured business process, wherein the received PPM is generated from a process model (PM) and a probabilistic graph including a probability, at each and every task of the semi-structured business process, for advancing to each of the other tasks of the semi-structured business process, and wherein the PM is derived from execution traces generated by one or more computer system elements generated during execution of a plurality of tasks of a semi-structured business process; receiving a status and content of an executing case instance of the business process; and updating at least one probability of the PPM using the probability distribution and the received status and content of said executing case instance of the business process.
13. A computer readable non-transitory storage medium embodying instructions executed by a plurality of processors for updating a probabilistic process model (PPM) of a semi-structured business process, the method comprising: receiving the PPM and at least one probability distribution corresponding to a decision node of the PPM, wherein the received PPM includes all possible execution sequences of the semi-structured business process, wherein the received PPM is generated from a process model (PM) and a probabilistic graph including a probability, at each and every task of the semi-structured business process, for advancing to each of the other tasks of the semi-structured business process, and wherein the PM is derived from execution traces generated by one or more computer system elements generated during execution of a plurality of tasks of a semi-structured business process; receiving a status and content of an executing case instance of the business process; and updating at least one probability of the PPM using the probability distribution and the received status and content of said executing case instance of the business process. 14. The computer readable storage medium of claim 13 , wherein updating further comprises mapping the PPM to an extended probabilistic process model with additional nodes representing states achievable through parallel paths in the PPM.