Recommend the best songs for an user

This model recommends the best songs for a listener based on the how the listener, and other listeners, rated songs.It is not based on any demographic information about listners or categorizing listeners by other means.
The data for this comes from the The Million Song DataSet, a freely-available collection of audio features and metadata for a million contemporary popular music tracks. The core of the dataset is the feature analysis and metadata for one million songs, provided by The Echo Nest. The dataset does not include any audio, only the derived features.

The user's ratings data is based on the Yahoo's Music User Rating dataset provided for the KDDCup 2011 competition.
Submitted By
Snap Analytx Inc.
Cost
$0/month
Date Added
6/17/2013
Source Code
Available
Languages
Java (Mahout)
Type
Recommendation
Algorithm
Collaborative Filtering
Analytic Engine
Hadoop
Try this Model Now!
Discuss this Model
Download Data Users Preferences
Download Table
Data Dictionary
Attribute Name Brief Description Type Range Low Range High
User IdThe unqiue id of each userInteger190
Song IDThe unqiue id of each songInteger14065
RatingRating assigned to a song by an userInteger1126
     
Download Table
Users - Songs Ratings
User Id Track/Album Song Name Rating
Notes:
  • The table shows the movie preferences for twenty (20) customers only.
  • The full set used to train the model consists of 4872 ratings by 90 users for 4065 songs. 'Download' to see the full data set.
  • The Track/Album and Song Name are not part of the data dictionary shown in the previous tab. i.e. if you download the table, the two attributes will not be present. The song name is just a "lookup" of the song id from the Song database