In this study, we investigate the task scheduling problem in heterogeneous computing environments and propose a novel scheduling algorithm, called the Artificial Immune System wit...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Recent years have seen the development of many graph clustering algorithms, which can identify community structure in networks. The vast majority of these only find disjoint commun...
In this paper, we investigate the emotion classification of web blog corpora using support vector machine (SVM) and conditional random field (CRF) machine learning techniques. The...