Deep Learning-Based Anime and Movie Recommendation System

Ramu, Pramod (2022) Deep Learning-Based Anime and Movie Recommendation System. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration manual) Download (1MB) | Preview

Abstract

In recent days it is observed that the over-the-top media platforms (OTT) ruling the entertainment sector which offers various contents such as films, tv series, animes and music directly to customers over internet. This created an interest to conduct a research in developing a recommendation system to generate top ’n’ recommendations of movies and animes for the users. Various machine learning models such as the k-nearest neighbors, collaborative filtering, content-based method and autoencoders have been used in generating the recommendations. But these models face data sparsity issues. So, there is an opportunity to address this problem as well as to generate a quality recommendations. So, in this project recommendation system using model-based collaborative filtering through deep learning has been proposed through which recommendations have been generated based on the user’s likes and interests on the anime and movies. Here the data will be preprocessed and then it is transformed by incorporating embedding techniques. The movie and anime dataset for the project is sourced from the open-source platform called Kaggle. The recommendations for the users are generated based on the ranking. The model is evaluated using Mean Squared Error(MSE) and Mean Absolute Error(MAE).The model successfully addressed the data sparsity problem by predicting the rating of the anime and movies as well as top ’n’ anime and movie recommendations have been generated.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Deep Learning; Data Sparsity; Recommendation System
Subjects:	G Geography. Anthropology. Recreation > GV Recreation Leisure Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Film Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	08 Mar 2023 15:46
Last Modified:	08 Mar 2023 15:46
URI:	https://norma.ncirl.ie/id/eprint/6280

Actions (login required)

View Item