Text Categorization Methods Using Topical Importance Characteristic

This paper presents a study, which evaluates the quality of well-know classification algorithms using Topical Importance Characteristic as a weighting scheme for features. For purposes of research, we used the Twenty Newsgroups dataset. The result of classifiers' performance on different subsets shows that method based on TIC outperforms approaches based on TF-IDF.