applications (e.g., software tools, news classification)? Dialectal or Modern Standard Arabic? Let me know which direction you are interested in. (PDF) Arabic Topic Identification: A Decade Scoping Review
approaches (e.g., algorithms, BERT, datasets)?
Arabic dialects vary significantly across 22 countries, creating difficulties in developing universal models, often necessitating country-specific or dialectal classification methods.
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.
applications (e.g., software tools, news classification)? Dialectal or Modern Standard Arabic? Let me know which direction you are interested in. (PDF) Arabic Topic Identification: A Decade Scoping Review
approaches (e.g., algorithms, BERT, datasets)? Arabic.doi
Arabic dialects vary significantly across 22 countries, creating difficulties in developing universal models, often necessitating country-specific or dialectal classification methods. applications (e
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. creating difficulties in developing universal models