feature selection (FS) is essential for effective and more accurate text classification (TC)
systems. This paper investigates the effectiveness of five commonly used FS methods for our …

Feature sub-set selection (FSS) is an important step for effective text classification (TC)
systems. This paper presents an empirical comparison of seventeen traditional FSS metrics …

Documents contain a vast amount of crucial human information. The substantial rise in the
number of electronic documents available for personal or public usage necessitates the …

Categorisation of text is significant trend that ultimately appears owing to the internet
revolution nowadays resulting in enormous amounts data that depend on various …

Purpose Owing to the huge volume of documents available on the internet, text classification
becomes a necessary task to handle these documents. To achieve optimal text classification …

Automatic document classification due to its various applications in data mining and
information technology is one of the important topics in computer science. Classification …

Statistical n-gram language modeling is applied in many domains like speech recognition,
language identification, machine translation, character recognition and topic classification …

Text classification (TC) concerns automatically assigning a class (category) label to a text
document, and has increasingly many applications, particularly in the domain of organizing …

In this paper, we propose a hybrid system for contextual and semantic indexing of Arabic
documents, bringing an improvement to classical models based on n-grams and the TFIDF …

I authorize the Arab Academy for Banking and Financial Sciences to lend this thesis to other
institutions or individuals for the purpose of scholarly research. I further authorize the Arab …