Developing a Centroid-Based Classification Model for Text Classification

In libraries, books are classified into some categories according to their topics in order to be found easily. However, due to the great expansion of Internet, there are enormous number of texts online and classifying them by hand is not possible. So, we need text classification algorithms. In literature, there are many types of text classification algorithms but they do not work well in skewed datasets. Skewed datasets are the datasets that have huge difference between number of documents of its classes. In this research, I proposed a new method called Gravitational Class Feature Classifier that solves skewed data problem.