1. A computer readable non-transitory storage medium embodying instructions executed by a plurality of processors for predictive analytics in a semi-structured business process, the method comprising: receiving execution traces generated by one or more computer system elements generated during the execution of a plurality of tasks of the semi-structured business process, wherein an outcome of the execution of each of the plurality of tasks is dependent upon one or more documents containing document content values, at least one of the execution traces including the document content value, wherein the document content value influenced the execution of the plurality of tasks; determining a process model from the execution traces, the process model comprising tasks at nodes of the semi-structured business process, wherein the determined process model includes all possible execution sequences of the semi-structured business process; determining a probabilistic graph including a probability, at each of the tasks of the semi-structured business process, for advancing to each of the other tasks of the semi-structured business process, wherein the probability is influenced by the document content value; and combining the process model and probabilistic graph to determine a probabilistic process model including probabilities and strengths of transitions between each and every task of the semi-structured business process.
9. The computer readable storage medium of claim 1 , the method further comprising constructing an extended probabilistic process model describing relations between the tasks of the business process based on the probabilistic process model, wherein the extended probabilistic process model enables predictive analytics in the business process based on content associated with the tasks.