This paper presents a method for incorporating natural language processing into existing text categorization procedures. Three aspects are considered in the investigation: (i) a m...
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...
Multi-document summarization is a challenge to information overload problem to provide a condensed text for a number of documents. Most multi-document summarization systems make u...
In this paper, we address a relatively new and interesting text categorization problem: classify a political blog as either liberal or conservative, based on its political leaning...
This paper describes a novel application of text categorization for mathematical word problems, namely Multiplicative Compare and Equal Group problems. The empirical results and a...
Suleyman Cetintas, Luo Si, Yan Ping Xin, Dake Zhan...