One of the major problems in CBIR is the so-called `semantic gap': the difference between low-level features, extracted from images, and the high-level `information need'...
Walter ten Brinke, David McG. Squire, John Bigelow
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
We propose a new method to measure “visualness” of concepts, that is, what extent concepts have visual characteristics. To know which concept has visually discriminative power...
This study describes experiments on automatic detection of semantic concepts, which are textual descriptions about the digital video content. The concepts can be further used in c...
Abstract. Due to the increasing amount and complexity of knowledge and information in many domains, students who self-regulate their study in e-learning scenarios often suffer from...