Initially popularized by Amazon.com, recommendation
technologies have become widespread over the past
several years, both in the industry and academia. The
traditional two-dimensional approach to recommender
systems, involving the dimensions of Users and Items, has
been subsequently extended to the multidimensional
approach supporting additional contextual dimensions
and OLAP-type aggregation capabilities. Furthermore,
the class of all possible recommendations available to the
users in traditional recommender systems is typically
determined by the vendor and is quite limited. In this
paper we address this limitation by proposing a query
language RQL that allows the users to formulate various
types of recommendation requests on their own. RQL
adapts OLAP queries to the domain of recommender
systems and, therefore, is able to support both the
traditional two-dimensional and the more complex
multidimensional recommender systems. The paper also
presents a recommendation algebra that allows mapping
RQL queries into the algebraic expressions for the query
processing purposes. Finally, the paper presents a
method for executing RQL queries.Information Systems Working Papers Serie