Consider a system, where each user enters the system, performs a series of predefined actions, and then exits.
For instance, consider a system with 5 predefined action. The action log of some user is detailed below:
enter, action 3, action 1, action 5, action 1, action 4, exit.
Notice that the order of actions matters.
Assume that we have the action logs for thousands of users, and we want to graphically model their behavior.
- What is the proper model, and
- How can we translate the action logs into this model?
More info. The Markov chain does not seem to be right, as Markov chains are memoryless, while in our system, the user remembers his/her actions, and decides on the next action based on the complete history after entering the system.
I guess Bayesian networks might be the appropriate choice, but I'm not sure. Specifically, I'm not sure if the acyclicity of Bayesian networks imposes a restriction on the desired model.