A Comparative Study of Sentiment-Aware Collaborative Filtering Algorithms for Arabic Recommendation Systems

The rapid proliferation of online information necessitates efficient Recommendation Systems (RSs) to assist users in discovering relevant content. While English-language RSs have received significant attention, research on Arabic RSs remains limited despite the increasing demand for Arabic digital c...

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Vydáno v:	IEEE access Ročník 12; s. 174441 - 174454
Hlavní autoři:	Al-Ghuribi, Sumaia Mohammed, Mohd Noah, Shahrul Azman, Mohammed, Mawal A., Tiwary, Neeraj, Saat, Nur Izyan Yasmin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Algorithms Arabic language Classification algorithms Collaboration Collaborative filtering Comparative studies deep autoencoder network Deep learning Filtration Machine learning algorithms Natural language processing Neural networks Prediction algorithms Ratings Recommender systems Reviews Sentiment analysis Support vector machines user reviews
ISSN:	2169-3536, 2169-3536
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