Classifier learning with data-sets that suffer from imbalanced class distributions is a
challenging problem in data mining community. This issue occurs when the number of …

In the pay-per-click online advertisement model, fraudulent publishers' presence is rare than
that of genuine publishers. This high-class imbalance between fraudulent and genuine …

Measuring the similarity between documents is an important operation in the text processing
field. In this paper, a new similarity measure is proposed. To compute the similarity between …

In this paper, we design and develop a movie-rating and review-summarization system in a
mobile environment. The movie-rating information is based on the sentiment-classification …

Universum, a collection of nonexamples that do not belong to any class of interest, has
become a new research topic in machine learning. This paper devises a semi-supervised …

Kernel association (KA) in statistical pattern recognition used for classification and prediction
have recently emerged in a machine learning and signal processing context. This survey …

Research of document classification is ongoing to employ the attention based-deep learning
algorithms and achieves impressive results. Owing to the complexity of the document …

Simulator imperfection, often known as model error, is ubiquitous in practical data
assimilation problems. Despite the enormous efforts dedicated to addressing this problem …

Text classification has been widely explored in natural language processing. In this article,
we propose a novel adaptive dense ensemble model (AdaDEM) for text classification, which …

A combination of classifiers leads to a substantial reduction of classification errors in a wide
range of applications. Among them, support vector machine (SVM) ensembles with bagging …