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\begin{center} \includegraphics[width=0.5\linewidth]{mangaki} \end{center} \vspace{5mm}

\noindent Mangaki is a manga/anime recommendation website: \url{http://mangaki.fr}.

Pitch

Everyone regularly ask themselves what movie, series or book they should watch next, according to their tastes. Mangaki wants to innovate access to culture by providing a unique user experience.

Innovation: Adaptive Testing for Personalized Recommendations {-}

In a typical recommendation website, a user rates a few anime (Favorite / Like / Dislike / Neutral / Want to see / Will not see) and the system provides suggestions of new works they might like. But newcomers usually have to rate a lot of items before they get satisfying recommendations.\bigskip

\noindent What distinguishes Mangaki from other recommender systems is a Tinder-like adaptive test for newcomers, asking the user « Did you like these works? ». This welcome test enables Mangaki's algorithm to automatically select works that will bring the most information about the user's tastes. This makes it possible to provide relevant recommendations faster.

\begin{figure}[h] \centering\includegraphics[width=0.9\linewidth]{decks} \end{figure}

Demo

\url{http://mangaki.fr/static/demo.mp4}

Technical features {-}

\noindent Mangaki is written in Python and relies on the following open source technologies:

  • the Django Web framework;
  • the machine learning library scikit-learn.

\noindent The code is entirely open source on \url{https://github.com/mangaki/mangaki}.

Main assets {-}

  • the welcome adaptive testing, relying on state-of-the-art algorithms from recent research ;
  • the core can be adapted to other databases (books, comics, video games, etc.)