In this demonstration paper we present MAPS, a novel system that combines approximate information retrieval and filtering functionality in a peer-to-peer setting. In MAPS, a user...
Christian Zimmer, Johannes Heinz, Christos Tryfono...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
This paper presents an analytical model to study how working sets scale with database size and other applications parameters in decision-support systems (DSS). The model uses appl...
Searching for images by using low-level visual features, such as color and texture, is known to be a powerful, yet imprecise, retrieval paradigm. The same is true if search relies...
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do thi...