Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data stre...
Eric P. Kasten, Philip K. McKinley, Stuart H. Gage
This paper deals with an acronym/definition extraction approach from textual data (corpora) and the disambiguation of these definitions (or expansions). Both steps of our global pr...
Developers of visual Interface Design Environments (IDEs), like Microsoft Visual Studio and Java NetBeans, are competing in producing pretty crowded graphical interfaces in order t...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...