The future of cybersecurity: Major role of artificial intelligence, machine learning, and deep learning in cyberspace(2019) https://link.springer.com/chapter/10.1007/978-981-10-8681-6_67
A Novel Hybrid Approach for Machine Learning Based Recommended Systems(2020) https://sersc.org/journals/index.php/IJGDC/article/view/11768
AMatrix factorization technique using parameter tuning of singular value decomposition for Recommender Systems (2021) https://www.proquest.com/openview/ba1d3a354df423b3ed4d30fb9169cac0/1?pq-origsite=gscholar&cbl=2045096
An implementation and combining of hybrid and content based and collaborative filtering algorithms for the higher performance of recommended systems (2021) https://link.springer.com/chapter/10.1007/978-3-030-76776-1_7
A Hybrid Approach to Resolve Data Sparsity and Cold Start Hassle in Recommender Systems (2022) https://link.springer.com/chapter/10.1007/978-981-16-5640-8_38
A Hybrid Approach for Predicting Diseases using Clustering and Classification Techniques (2022)https://ieeexplore.ieee.org/abstract/document/9752552
A Survey on Deep Learning Prediction Techniques for Plant Contagion (2022) https://ieeexplore.ieee.org/abstract/document/10009599
A Naïve Bayes Approach for Predicting the Skin Allergy Diseases(2023) https://link.springer.com/chapter/10.1007/978-981-19-7402-1_35
Enhancing Recommender Systems with Hidden User Interests and Machine Learning: A Study of Multi-Label Classifiers (2024) https://ieeexplore.ieee.org/abstract/document/10512060
Optimizing Recommendation Systems: A Hybrid Approach for Improved Accuracy (2024) https://ieeexplore.ieee.org/abstract/document/10675645
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