A simplistic anime recommendation system: try it at aqua-recommend.net
The core of the system is a set of well-known recommendation algorithms, using rating data from MyAnimeList.
Currently implemented algorithms are:
- co-occurrency collaborative filtering ("other users also liked..." recommendations)
"Item-based top-N recommendation algorithms" by Mukund Deshpande and George Karypis (2004) - memory-based colleborative filtering using vector dot product as similarity measure
WikiPedia link - latent factor decomposition (LFD) matrix factorization using alternating least squares
blog.insightdatascience.com link - memory-based collaborative filtering using LFD output vectors instead of the raw rating vectors
In my completely unbiased evaluation, Aqua provides decent recommendations, but keep in mind that this is mostly a pet project to learn more about fields I was not familiar with before (recommendations, machine learning) and to check out some technologies (Clojure, React, React Native). In other words: I think the end result is useful, but creating a finished product was never the goal.
There ahe instructions to enable Machine Optimised System Libraries.
On Ubuntu it might be necessary to:
- manually install libgfortran 3
- manually symlink the libraries under /usr/lib
Copyright 2017 Mattia Barbon
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