Weirdness Coefficient as a Feature Selection Method for Arabic Special Domain Text Classification

Given the importance of organizing and managing the rapid growth in knowledge of Arabic electronic content, this study introduces the Weirdness Coefficient (W) as a new feature selection method for Arabic special domain text classification. The proposed method was used to classify a dataset comprising five Islamic topics using Naive base (NB) and K-nearest neighbor (K-NN) classifiers, and three representation schemas. The results were also compared with a well-known feature selection method, Chi-squared. In addition to its simplicity in computation, the Weirdness Coefficient showed promising classification accuracy.