Abstract: Recommender systems are software tools used to leverage different strategies to generate suggestions for movies and other entities and make them available to users. Hybrid recommender systems combine two or more recommendation systems in different ways to take advantage of their complementary benefits. This systematic literature review reveals the latest technology in hybrid recommender systems over the last decade. An overview of relevant data mining and recommended techniques used to address and overcome the most relevant issues under consideration. It also considers the hybridization class to which each hybrid recommender belongs, the application domain, the evaluation process, and the proposed future research direction. Based on our results, most studies combine collaborative filtering with other techniques and are often weighted.
The Hybrid Recommender System is a hot topic and provides a good foundation for responding to new opportunities by exploring new opportunities, Contextualization recommendations, embedding parallel hybrid algorithms, and processing large datasets.
Keywords: Movie Recommender System, Hybrid Recommender System, Content – Based System, Collaborative based System.
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DOI:
10.17148/IJARCCE.2022.11618
