Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 23, December 2021

Anime4You: An Intelligent Analytical Framework for Anime Recommendation
and Personalization using AI and Big Data Analysis


Kaiho Cheung1, Ishmael Rico2, Tao Li3 and Yu Sun4, 1Sentinel Secondary, Canada, 2University of California, USA, 3Purdue University, USA, 4California State Polytechnic University, USA


In recent years the popularity of anime has steadily grown. Similar to other forms of media consumers often face a pressing issue: “What do I watch next?”. In this study, we thoroughly examined the current method of solving this issue and determined that the learning curve to effectively utilize the current solution is too high. We developed a program to ensure easier answers to the issue. The program uses a Python-based machine learning algorithm from ScikitLearn and data from My Animelist to create an accurate model that delivers what consumers want, good recommendations [9]. We also carried out different experiments with several iterations to study the difference in accuracy when applying different factors. Through these tests, we have successfully created a reliable Support vector machine model with 57% accuracy in recommending users what to watch.


Machine learning, anime, recommendations, Python.