  Multi-criteria decision making has been made possible with the advent of
skyline queries. However, processing such queries for high dimensional datasets
remains a time consuming task. Real-time applications are thus infeasible,
especially for non-indexed skyline techniques where the datasets arrive online.
In this paper, we propose a caching mechanism that uses the semantics of
previous skyline queries to improve the processing time of a new query. In
addition to exact queries, utilizing such special semantics allow accelerating
related queries. We achieve this by generating partial result sets guaranteed
to be in the skyline sets. We also propose an index structure for efficient
organization of the cached queries. Experiments on synthetic and real datasets
show the effectiveness and scalability of our proposed methods.
