  We present a method to geometrize massive data sets from search engines query
logs. For this purpose, a macrodynamic-like quantitative model of the
Information Retrieval (IR) process is developed, whose paradigm is inspired by
basic constructions of Einstein's general relativity theory in which all IR
objects are uniformly placed in a common Room. The Room has a structure similar
to Einsteinian spacetime, namely that of a smooth manifold. Documents and
queries are treated as matter objects and sources of material fields.
Relevance, the central notion of IR, becomes a dynamical issue controlled by
both gravitation (or, more precisely, as the motion in a curved spacetime) and
forces originating from the interactions of matter fields. The spatio-temporal
description ascribes dynamics to any document or query, thus providing a
uniform description for documents of both initially static and dynamical
nature. Within the IR context, the techniques presented are based on two ideas.
The first is the placement of all objects participating in IR into a common
continuous space. The second idea is the `objectivization' of the IR process;
instead of expressing users' wishes, we consider the overall IR as an objective
physical process, representing the IR process in terms of motion in a given
external-fields configuration. Various semantic environments are treated as
various IR universes.
