  The exploding growth of digital data in the information era and its
immeasurable potential value has called for different types of data-driven
techniques to exploit its value for further applications. Information
visualization and data mining are two research field with such goal. While the
two communities advocates different approaches of problem solving, the vision
of combining the sophisticated algorithmic techniques from data mining as well
as the intuitivity and interactivity of information visualization is tempting.
In this paper, we attempt to survey recent researches and real world systems
integrating the wisdom in two fields towards more effective and efficient data
analytics. More specifically, we study the intersection from a data mining
point of view, explore how information visualization can be used to complement
and improve different stages of data mining through established theories for
optimized visual presentation as well as practical toolsets for rapid
development. We organize the survey by identifying three main stages of typical
process of data mining, the preliminary analysis of data, the model
construction, as well as the model evaluation, and study how each stage can
benefit from information visualization.
