Arabic.doi

While there is a growing number of Arabic NLP datasets, there is a lack of high-quality, large-scale, and diverse datasets for certain domains.

Arabic topic identification is a specialized field within Natural Language Processing (NLP) that involves classifying Arabic text into specific categories (e.g., politics, sports, culture). Given the language's unique morphological and syntactic structure, standard English-centric NLP techniques often underperform, requiring dedicated approaches to handle its complexity. Arabic.doi

Techniques like Term Frequency-Inverse Document Frequency (TFIDF) and k-Nearest Neighbors (kNN) are used, often combined with triggers (i.e., Average Mutual Information) to improve results. While there is a growing number of Arabic