  Even the best information retrieval model cannot always identify the most
useful answers to a user query. This is in particular the case with web search
systems, where it is known that users tend to minimise their effort to access
relevant information. It is, however, believed that the interaction between
users and a retrieval system, such as a web search engine, can be exploited to
provide better answers to users. Interactive Information Retrieval (IR)
systems, in which users access information through a series of interactions
with the search system, are concerned with building models for IR, where
interaction plays a central role. There are many possible interactions between
a user and a search system, ranging from query (re)formulation to relevance
feedback. However, capturing them within a single framework is difficult and
previously proposed approaches have mostly focused on relevance feedback. In
this paper, we propose a general framework for interactive IR that is able to
capture the full interaction process in a principled way. Our approach relies
upon a generalisation of the probability framework of quantum physics, whose
strong geometric component can be a key towards a successful interactive IR
model.
