A Hybrid Approach to Service Recommendation Based on Network Representation LearningV5.0

Citation Author(s):
Hao
Wu
Submitted by:
Hao Wu
Last updated:
Mon, 04/08/2019 - 07:38
DOI:
10.21227/0evt-b498
License:
Creative Commons Attribution
82 Views
Categories:
Computational Intelligence
Keywords:
Recommender System
0
0 ratings - Please login to submit your rating.
ACCESS DATASET CITE SHARE/EMBED

Abstract 

A Hybrid Approach to Service Recommendation Based on Network Representation Learning

Instructions: 

  1892 users
   17632 artists
     
   12717 bi-directional user friend relations, i.e. 25434 (user_i, user_j) pairs
         avg. 13.443 friend relations per user
        
   92834 user-listened artist relations, i.e. tuples [user, artist, listeningCount]
         avg. 49.067 artists most listened by each user
         avg. 5.265 users who listened each artist
           
   11946 tags 
  
  186479 tag assignments (tas), i.e. tuples [user, tag, artist]
         avg. 98.562 tas per user
         avg. 14.891 tas per artist
         avg. 18.930 distinct tags used by each user
         avg. 8.764 distinct tags used for each artist

Dataset Files

    Files have not been uploaded for this dataset

    Documentation

    AttachmentSize
    File tags.txt228.97 KB
    File user_artists.txt1.24 MB
    File user_friends.txt245.67 KB
    File user_taggedartists.txt4.16 MB

     

    QUESTIONS?