movie recommendation research paper

Oct 13, 2020 · This paper classifies collaborative filtering using various approaches like matrix factorization, user-based recommendation, item-based recommendation. This survey also tells the road map for ...

This research paper presents a comprehensive literature review of various movie recommendation systems, including techniques such as sentiment analysis of comments, movie trailer data, facial expressions, browsing history, and view percentage. The paper also compares various recommenders based on deep learning and swarm algorithms. Furthermore, this paper provides a novel approach for movie ...

Feb 7, 2024 · This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main ...

progression of movie recommendation systems, presenting a promising avenue for elevating user experience within the domain of content-based movie recommendations. These are the research works we came across for the development of this movie recommendation system using content-based and collaborative filtering. IV. WORKING:

Dec 23, 2021 · PDF | A recommender system, also known as a recommendation system, is a type of information filtering system that attempts to forecast a user's rating... | Find, read and cite all the research you ...

1.1.2) Movie Recommendation Recommendation systems are being used by a lot of businesses to improve customer interaction and the purchasing experience. The most significant advantages of recommendation systems are client happiness and income. A very effective and crucial mechanism is the movie recommendation system.

This research paper looks at movie recommendations and the reasoning behind them, as well as common movie recommendation systems, problems with traditional film recommendation engines, and other relevant topics. Among the well-known datasets are the Movielens dataset, the TMDB Movie Dataset, as well as the Netflix dataset.

Jun 29, 2022 · Movie recommender systems are meant to give suggestions to the users based on the features they love the most. A highly performing movie recommendation will suggest movies that match the similarities with the highest degree of performance. This study conducts a systematic literature review on movie recommender systems. It highlights the filtering criteria in the recommender systems, algorithms ...

offering valuable insights for further research in recommendation systems. Jiang et al. [2]’s study addresses scalability and practical usage feedback in Movie Recommendation Systems. It proposes a high-efficient recommendation algorithm based on user clustering. The method achieves comparable

been proposed for movie recommendation, including collaborative filtering, content-based filtering, hybrid approaches, and others. ollaborative filtering is a popular approach in recommendation systems that uses user-item ratings to generate recommendations. In a research paper by reese et al. ( í õ õ ô), ollaborative filtering was used to