  We present a system for summarization and interactive exploration of
high-valued aggregate query answers to make a large set of possible answers
more informative to the user. Our system outputs a set of clusters on the
high-valued query answers showing their common properties such that the
clusters are diverse as much as possible to avoid repeating information, and
cover a certain number of top original answers as indicated by the user.
Further, the system facilitates interactive exploration of the query answers by
helping the user (i) choose combinations of parameters for clustering, (ii)
inspect the clusters as well as the elements they contain, and (iii) visualize
how changes in parameters affect clustering. We define optimization problems,
study their complexity, explore properties of the solutions investigating the
semi-lattice structure on the clusters, and propose efficient algorithms and
optimizations to achieve these goals. We evaluate our techniques experimentally
and discuss our prototype with a graphical user interface that facilitates this
interactive exploration. A user study is conducted to evaluate the usability of
our approach.
