This paper explores the incorporation of prior knowledge into support vector machines as a
means of compensating for a shortage of training data in text categorization. The prior …

The World Wide Web has many document repositories that can act as valuable sources of
additional data for various machine learning tasks. In this paper, we propose a method of …

This paper proposes a new approach for text categorization, based on a feature projection
technique. In our approach, training data are represented as the projections of training …

In this paper, we conducted an experiment to build a classification model that combines
different techniques in most of the Natural Language Processing Tasks. We used the word …

Most of the research on text categorization has focused on classifying text documents into a
set of categories with no structural relationships among them (flat classification). However, in …

A massive rise in web-based online content today pushes businesses to implement new
approaches and resources that might support better navigation, processing, and handling of …

Text Categorization (TC), also known as Text Classification, is the task of automatically
classifying a set of text documents into different categories from a predefined set. If a …

With the fast increase of the documents, using Text Document Classificafion (TDC) methods
has become a crucial matter. This paper presented a hybrid model of Invasive Weed …

Feature selection and extraction are frequently used solutions to overcome the curse of
dimensionality in text classification problems. We introduce an extraction method that …