Text document classification approaches are designed to categorise documents into
predefined classes. These approaches have two main components: document …

Background The growing number of medical literature and textual data in online repositories
led to an exponential increase in the workload of researchers involved in citation screening …

The classification of opinion based on customer reviews is a complex process owing to high
dimensionality. In this study, our objective is to select the minimum number of features to …

Firstly, a new concept of term frequency difference factor is proposed to balance the
influences of term frequency and document frequency on feature selection. Secondly, the …

This paper proposes four novel term evaluation metrics to represent documents in the text
categorization where class distribution is imbalanced. These metrics are achieved from the …

Background: Term-weighting plays a key role in detecting emotion in texts. Studies in term-
weighting schemes aim to improve short text classification by distinguishing terms …

Term weighting in text classification plays a crucial role in determining the accuracy of text
classifiers based on supervised machine-learning techniques. Similarly, its importance in …

Imbalanced sentiment is one of the key classification issues. Many studies have proposed
imbalanced sentiment classification improvements, but the topic remains problematic as a …

Lexicon-based approaches to Document Classification are widely used, but the manual
construction of lexicons can be time-consuming and resource-intensive. In this paper, we …

Automatic web page classification has become inevitable for web directories due to the
multitude of web pages in the World Wide Web. In this paper an improved Term Weighting …