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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Bibliographic Details
Published in:	IEEE access Vol. 12; pp. 174441 - 174454
Main Authors:	Al-Ghuribi, Sumaia Mohammed, Mohd Noah, Shahrul Azman, Mohammed, Mawal A., Tiwary, Neeraj, Saat, Nur Izyan Yasmin
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
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