Feb 26th 2018
Deepnify wins ACM Recommendation WSDM Conference Challenge
By: Krista Caldwell
Congratulations to Deepnify's Nima Shahbazi for winning the ACM Recommendation WSDM Conference Challenge last month and presented his result at the most prestigious WSDM Conference in LA.

The Competition Challenge
While the public's now listening to all kinds of music, recommendation algorithms still struggle in key areas. Without enough historical data, how would an algorithm know if listeners will like a new song or a new artist? And, how would it know what songs to recommend brand new users? Your task to to solve the abovementioned challenges and build a better music recommendation system.

Competing against 1081 teams from universities around the world, Nima's solution ranked 2nd with 0.00091 difference from the first place team.

On the Google Scholar data mining conferences rankings, the ACM WSDM conference is 3rd. You can read Nima's published Paper on Truncated SVD-based Feature Engineering for Music Recommendation on the ACM website.

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