We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of informat...
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
This paper presents a method to speed up support vector classification, especially important when data is highdimensional. Unlike previous approaches which focus on less support v...
This paper presents an unsupervised discretization method that performs density estimation for univariate data. The subintervals that the discretization produces can be used as the...
This paper introduces a strategy and its theory proof to transform non-linear concept graph: Directed Acyclic Concept Graph (DACG) into a linear concept tree. The transformation i...