Exploiting Aesthetic Features in Visual Contents for Movie Recommendation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2910722
Abstract: As one of the most widely used recommender systems, movie recommendation plays an important role in our life. However, the data sparsity problem severely hinders the effectiveness of personalized movie recommendation, which requires more rich… read more here.
Keywords: movie; exploiting aesthetic; aesthetic features; visual contents ... See more keywords
An Integrated PCA-DAEGCN Model for Movie Recommendation in the Social Internet of Things
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3111614
Abstract: With the development of the Social Internet of Things (SIoT) and mobile technologies in recent years, movie recommendation systems have become popular in online movie recommendation that users may like to watch based on their… read more here.
Keywords: pca daegcn; movie; model; internet things ... See more keywords
Multimodal Movie Recommendation With Multitasking Architecture and Learning User–Movie Representation: An Empirical Study
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Computational Social Systems"
DOI: 10.1109/tcss.2025.3539884
Abstract: With the increasing availability of multimodal movie data, there is a growing interest in leveraging these data to improve movie recommendations. In the recent era, due to the increase in the number of users and… read more here.
Keywords: movie; multimodal movie; movie recommendation; approach ... See more keywords
Personalized Movie Recommendation Method Based on Deep Learning
Sign Up to like & getrecommendations! Published in 2021 at "Mathematical Problems in Engineering"
DOI: 10.1155/2021/6694237
Abstract: With the rapid development of network technology and entertainment creation, the types of movies have become more and more diverse, which makes users wonder how to choose the type of movies. In order to improve… read more here.
Keywords: recommendation; movie recommendation; deep learning; personalized movie ... See more keywords
The movie recommendation algorithm based on the TransD model and AIGC empowerment and its application effectiveness analysis
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DOI: 10.1371/journal.pone.0333607
Abstract: This study aims to enhance the recommendation system’s capability in addressing cold start issues, semantic understanding, and modeling the diversity of user interests. The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph… read more here.
Keywords: recommendation; movie recommendation; recommendation algorithm; transd model ... See more keywords
Hash-based and privacy-aware movie recommendations in a big data environment
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Embedded Systems"
DOI: 10.1504/ijes.2020.10025052
Abstract: Movie recommendation is an important activity in the people's daily entertainment. Typically, through analysing the users' ever-watched movie list, a movie recommender system can recommend appropriate new movies to the target user. However, traditional movie… read more here.
Keywords: privacy aware; recommendation; hash based; movie recommendation ... See more keywords
Movie Recommendation through Multiple Bias Analysis
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11062817
Abstract: A recommender system (RS) refers to an agent that recommends items that are suitable for users, and it is implemented through collaborative filtering (CF). CF has a limitation in improving the accuracy of recommendations based… read more here.
Keywords: multiple bias; bias analysis; analysis; movie recommendation ... See more keywords
Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems
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DOI: 10.3390/app14031155
Abstract: In the era of big data, effective recommendation systems are essential for providing users with personalized content and reducing search time on online platforms. Traditional collaborative filtering (CF) methods face challenges like data sparsity and… read more here.
Keywords: movie recommendation; recommendation systems; reinforcement learning; recommendation ... See more keywords