From a user model for query sessions to session rank biased precision (sRBP)

To satisfy their information needs, users usually carry out searches on retrieval systems by continuously trading off between the examination of search results retrieved by under-specified queries and the refinement of these queries through reformulation. In Information Retrieval (IR), a series of query reformulations is known as a query-session. Research in IR evaluation has traditionally been focused on the development of measures for the ad hoc task, for which a retrieval system aims to retrieve the best documents for a single query. Thus, most IR evaluation measures, with a few exceptions, are not suitable to evaluate retrieval scenarios that call for multiple refinements over a query-session. In this paper, by formally modeling a user's expected behaviour over query-sessions, we derive a session-based evaluation measure, which results in a generalization of the evaluation measure Rank Biased Precision (RBP …