In this paper we present an algorithm for automatic extraction of textual elements, namely titles and full text, associated with news stories in news web pages. We propose a super...
In this work we show that verbs reliably represent texts when machine learning algorithms are used to learn opinions. We identify semantic verb categories that capture essential pr...
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...