Modeling Decision Points in User Search Behavior
Department of Computing and Information Systems,
The University of Melbourne,
Victoria 3010, Australia.
School of Computer Science and Information Technology,
Victoria 3001, Australia.
Proc. 5th International Interaction in Context Symposium,
Regensburg, August 2014, pages 239-242.
Understanding and modeling user behavior is critical to designing
search systems: it allows us to drive batch evaluations, predict how
users would respond to changes in systems or interfaces, and suggest
ideas for improvement.
In this work we present a comprehensive model of the interactions
between a searcher and a search engine, and the decisions users make in
The model is designed to deal only with observable phenomena.
Based on data from a user study, we are therefore able to make initial
estimates of the probabilities associated with various decision points.
More sophisticated estimates of these decision points could include
probabilities conditioned on some amount of search activity state.
In particular, we suggest that one important part of this state is the
amount of utility a user is seeking, and how much of this they have
collected so far.
We propose an experiment to test this, and to elucidate other factors
which influence user actions.