As the huge dimensionality of textual data restrains the classification accuracy, it is essential
to apply feature selection (FS) methods as dimension reduction step in text classification …

Text classification is a very important topic in the current era due to the high volume of
textual data and handling. Feature selection is one of the most important steps in text …

Automatic authorship identification is a challenging task that has been the focus of extensive
research in natural language processing. Regardless of the progress made in attributing …

In the field of text classification, some of the datasets are unbalanced datasets. In these
datasets, feature selection stage is important to increase performance. There are many …

In this paper, we introduce a new method of representation learning that aims to embed
documents in a stylometric space. Previous studies in the field of authorship analysis …

The anonymity on the Darknet allows vendors to stay undetected by using multiple vendor
aliases or frequently migrating between markets. Consequently, illegal markets and their …

Authorship Analysis (AA) is a natural language processing field that examines the previous
works of writers to identify the author of a text based on its features. Studies in authorship …

With the rapid development of digitalization, information security becomes more and more
important. User authentication is a significant line of defense. During the past few years …

Author identification is an important aspect of literary analysis, studied in natural language
processing (NLP). It aids identify the most probable author of articles, news texts or social …

Natural language processing (NLP) is the a types of artificial intelligence approach used to
maintain the decision making and data interaction process with high accuracy and reliability …