Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
The extensive work on Knowledge Engineering in the 1990s has resulted in a systematic analysis of task-types, and the corresponding problem solving methods that can be deployed fo...
Frank van Harmelen, Annette ten Teije, Holger Wach...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Science is increasingly driven by data collected automatically from arrays of inexpensive sensors. The collected data volumes require a different approach from the scientists'...
Stuart Ozer, Jim Gray, Alexander S. Szalay, Andrea...
Parallelism can be used for major performance improvement in large Data warehouses (DW) with performance and scalability challenges. A simple low-cost shared-nothing architecture ...