This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
Machine-understandable data constitutes the foundation for the Semantic Web. This paper presents a viable way for authoring and annotating Semantic Documents on the desktop. In our...
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
There is a signi cant di erence between documentinglarge programs and documenting small ones. By large programs we mean on the order of 1,000,000 lines, usually written by many di...