In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Most studies in statistical or machine learning based authorship attribution focus on two or a few authors. This leads to an overestimation of the importance of the features extra...
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
— Fundamental to the problem of lifelong machine learning is how to consolidate the knowledge of a learned task within a long-term memory structure (domain knowledge) without the...
A new approach to the Text Categorization problem is here presented. It is called Gaussian Weighting and it is a supervised learning algorithm that, during the training phase, est...