p. 171-174
This paper proposes a formal concept of stochastic workflow activity-to-performer affiliation network model. The proposed model is based upon the conceptual formalism of an extended information control net [20] that is revised from the original so as to adopt the probability theory to the activity-to-performer bindings in specifying a workflow procedure. In general, when a workflow management engine enacts a workflow procedure, it has to bind each of the corresponding activities up with a performer, together, and which is embodied through an activity-to-performer binding mechanism. As a more sophisticated approach, it is important to apply the probability theory to specify the activity-to-performer bindings, and which is called the probabilistic activity-to-performer bindings. In consequence, this paper expatiates the formal definition of a stochastic workflow activity-to-performer affiliation model that is algorithmically discovered from a set of the probabilistic activity-to-performer bindings specified in an extended information control net, and summarizes the implications of the proposed model in terms of analyzing and quantifying the human-centered knowledge in a workflow-supported organization, such as probabilistic closeness, degree, and betweenness centrality measures, affiliation network dynamics, and degree of fidelity.
