Modeling Knowledge Worker Activity

This paper describes an approach to constructing a probabilistic process model representing knowledge worker activity out of a log of primitive events, such as e-mails, web page visits and document accesses. Firstly, we present the process of enriching the primitive events into abstract actions, executed in different contexts. We explain the process of obtaining both context and action for each event by clustering the events via two different views. Secondly, we present an application of probabilistic deterministic finite automata to model the transitions between consecutive actions within the same context and demonstrate the approach on real-world knowledge worker data for the purpose of understanding knowledge processes and demonstrating the feasibility of the proposed approach, where a process model is constructed out of low-level events.