Graph Convolutional Neural Network for Multimodal Movie Recommendation

Author:

Mondal Prabir1ORCID,Chakder Daipayan1ORCID,Raj Subham1ORCID,Saha Sriparna1ORCID,Onoe Naoyuki2ORCID

Affiliation:

1. Computer Science and Engineering, Indian Institute of Technology, Patna, Patna, Bihar, India

2. Research and Development, Sony Research India, Bengaluru, Karnataka, India

Publisher

ACM

Reference37 articles.

1. New Recommendation Techniques for Multicriteria Rating Systems

2. Multi-model deep learning approach for collaborative filtering recommendation system;Aljunid Mohammed Fadhel;CAAI Transactions on Intelligence Technology,2020

3. Mohammed Fadhel Aljunid and DH Manjaiah . 2019. Movie recommender system based on collaborative filtering using apache spark . In Data management, analytics and innovation . Springer , 283--295. Mohammed Fadhel Aljunid and DH Manjaiah. 2019. Movie recommender system based on collaborative filtering using apache spark. In Data management, analytics and innovation. Springer, 283--295.

4. Autoencoders and recommender systems: COFILS approach;Barbieri Julio;Expert Systems with Applications,2017

5. Root mean square error (RMSE) or mean absolute error (MAE);Chai Tianfeng;Geoscientific Model Development Discussions,2014

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1. Optimizing Movie Selections: A Multi-Task, Multi-Modal Framework with Strategies for Missing Modality Challenges;Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing;2024-04-08

2. Impulsion of Movie’s Content-Based Factors in Multi-modal Movie Recommendation System;Communications in Computer and Information Science;2023-11-26

3. An overview of video recommender systems: state-of-the-art and research issues;Frontiers in Big Data;2023-10-30

4. A Multi-modal Multi-task based Approach for Movie Recommendation;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

5. Genre Effect Towards Developing a Multi-Modal Movie Recommendation System in Indian Setting;IEEE Transactions on Consumer Electronics;2023

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