As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
In this paper, an evaluation is presented of a framework that supports flexible content repurposing. Unlike the usual practice where content components, such as slides, images, def...
We propose a framework to learn scene semantics from surveillance videos. Using the learnt scene semantics, a video analyst can efficiently and effectively retrieve the hidden sem...
We propose a new distributed, fault-tolerant Peer-to-Peer index structure for resource discovery applications called the P-tree. P-trees efficiently support range queries in addit...
Adina Crainiceanu, Prakash Linga, Johannes Gehrke,...
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...