This paper presents a principled framework for efficient processing of ad-hoc top-k (ranking) aggregate queries, which provide the k groups with the highest aggregates as results....
Chengkai Li, Kevin Chen-Chuan Chang, Ihab F. Ilyas
We define a framework for static optimization of sliding window conjunctive queries over infinite streams. When computational resources are sufficient, we propose that the goal of...
We present a framework which allows the user to access and manipulate data uniformly, regardless of whether it resides in a database or in the file system (or in both). A key issu...
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Abstract— Developing a full-fledged cost-based XQuery optimizer is a fairly complex task. Nowadays, there is little knowledge concerning suitable cost formulae and optimization ...