This paper presents a novel way of improving POS tagging on heterogeneous data. First, two separate models are trained (generalized and domain-specific) from the same data set by...
We describe a framework called the Uni-Level Description (ULD) for accurately representing information from a broad range of data models. The ULD extends previous metadata-model a...
Abstract. The OMG’s Model-Driven Architecture focusses on the evolution and integration of applications across heterogeneous middleware platforms. Presently available instances o...
In this article, we develop a new method to segment Q-Ball imaging (QBI) data. We first estimate the orientation distribution function (ODF) using a fast and robust spherical harmo...
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...