[Mangaki challenge] Anime and manga recommendation

Mangaki.fr is an online platform where users can (1) provide ratings of anime and manga; and (2) receive personalized recommendations of what to watch next. It is being actively developed by a community of French crazy students, and the whole code of the platform is available on GitHub, so interested users can improve the machine learning algorithms of Mangaki.

In this challenge, in order to win (and show your supremacy to the world), you will have to predict the ratings of users over unwatched anime and manga. The ratings are provided by the actual users.

You are more than welcome to look for extra sources of data in order to improve your score. All programming languages are allowed. Just find the one that works best for you! Winners will be provided an opportunity to promote their solutions on University of Big Data.

Problem type
Classification
Evaluation metric
Area under the ROC curve (AUC)
Competition status
Active
Started
2017/07/02 00:00 (Japan Standard Time)
Ends
2017/10/01 23:59 (Japan Standard Time)
Public/Private
Public
Invitation setting
Open to everyone

Download dataset and submission

You are required to sign up and log in to downalod the dataset and make a submission.

Intermediate ranking

Intermediate rank Nickname Intermediate score
1 GeniusIke 0.85567
2 ηzw 0.83325
3 lapis_zero09 0.82744
4 BC 0.82411
5 CVxTz 0.82251
6 karekyasu 0.82076
7 Arson, Chen 0.81280
8 himkt 0.79639
9 my 0.79030
10 chvsp 0.76188
11 ielmansouri 0.71621
12 arig 0.63469
13 lyxia 0.58302
14 juanbits 0.56456
15 Anton Petrov 0.55888
16 fnareoh 0.52188
17 kazuma_desu 0.50207
18 Dawars 0.50129
19 9mwebmail 0.50008
20 Fistine 0.50000
20 kyegorov 0.50000
22 Sablier 0.49864
23 gx 0.49751
24 admin 0.49630
24 doraemon 0.49630
24 EstelleKts 0.49630

This leaderboard is calculated on the latest submissions.
The intermediate scores are calculated using 50% of the test dataset, and the final scores are calculated using the other 50%.
Final ranks are determined according to the final scores.

Scores over time (Intermediate score)

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