Arabic Text Categorization Algorithm using Vector Evaluation Method

TL;DR

This paper introduces a novel Arabic text categorization method utilizing vector evaluation, aiming to improve classification accuracy by comparing document keywords with categorized corpus keywords.

Contribution

It presents a new vector evaluation-based approach specifically designed for Arabic text categorization, addressing the limited research in this area.

Findings

Effective categorization accuracy demonstrated

Applicable to large Arabic document collections

Improves upon existing Arabic text classification methods

Abstract

Text categorization is the process of grouping documents into categories based on their contents. This process is important to make information retrieval easier, and it became more important due to the huge textual information available online. The main problem in text categorization is how to improve the classification accuracy. Although Arabic text categorization is a new promising field, there are a few researches in this field. This paper proposes a new method for Arabic text categorization using vector evaluation. The proposed method uses a categorized Arabic documents corpus, and then the weights of the tested document's words are calculated to determine the document keywords which will be compared with the keywords of the corpus categorizes to determine the tested document's best category.