Given the ubiquity of handwritten documents in human transactions, Optical Character
Recognition (OCR) of documents have invaluable practical worth. Optical character …

The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

With the rapid development of the internet technology, a large amount of internet text data
can be obtained. The text classification (TC) technology plays a very important role in …

Multi-instance learning (MIL) is a useful tool for tackling labeling ambiguity in learning
because it allows a bag of instances to share one label. Bag mapping transforms a bag into …

Text classification is a process of classifying documents into predefined categories through
different classifiers learned from labelled or unlabelled training samples. Many researchers …

Detecting cybersecurity intelligence (CSI) on social media such as Twitter is crucial because
it allows security experts to respond cyber threats in advance. In this paper, we devise a new …

The effective representation of the relationship between the documents and their contents is
crucial to increase classification performance of text documents in the text classification …

Text classification is one of the popular high dimensional classification problems where
providing better feature vector representations explicitly improve classification …

The rapid growth of textual data has made text classification a critical research area in the
field of Natural Language Processing. Traditional Graph Convolutional Networks (GCN) face …

In order to solve the problem that traditional short text classification methods do not perform
well on short text due to the data sparsity and insufficient semantic features, we propose a …