This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Meeting summarization provides a concise and informative summary for the lengthy meetings and is an effective tool for efficient information access. In this paper, we focus on ext...