  The session search task aims at best serving the user's information need
given her previous search behavior during the session. We propose an extended
relevance model that captures the user's dynamic information need in the
session. Our relevance modelling approach is directly driven by the user's
query reformulation (change) decisions and the estimate of how much the user's
search behavior affects such decisions. Overall, we demonstrate that, the
proposed approach significantly boosts session search performance.
