  Extracting the relevant information by exploiting the spatial data warehouse
becomes increasingly hard. In fact, because of the enormous amount of data
stored in the spatial data warehouse, the user, usually, don't know what part
of the cube contain the relevant information and what the forthcoming query
should be. As a solution, we propose to study the similarity between the
behaviors of the users, in term of the spatial MDX queries launched on the
system, as a basis to recommend the next relevant MDX query to the current
user. This paper introduces a new similarity measure for comparing spatial MDX
queries. The proposed similarity measure could directly support the development
of spatial personalization approaches. The proposed similarity measure takes
into account the basic components of the similarity assessment models: the
topology, the direction and the distance.
