From Popularity to Personality — A Heuristic Music Recommendation Method for Niche Market

  • Jun-Lin ZhouEmail author
  • Yan Fu
  • Hua Lu
  • Chong-Jing Sun
Short Paper


In most current recommender systems, the goal to accurately predict what people want leads to the tendency to recommend popular items, which is less helpful in revealing user’s personality, especially to new users. In this paper, we propose a heuristic music recommendation method for niche market by focusing on how to identify user’s personality as soon as possible. Instead of trying to improve algorithm's performance on new users by recommending the most popular items, we work on how to make them “familiar” with the system earlier. The method is more suitable for brand-new users, and gives a hint to solve the cold start problem. In real applications it is better to combine it with a traditional approach.


music recommendation system niche market item popularity user personality 

Supplementary material

11390_2011_180_MOESM1_ESM.pdf (143 kb)
(PDF 143 KB)


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Copyright information

© Springer Science+Business Media, LLC & Science Press, China 2011

Authors and Affiliations

  1. 1.Web Sciences CenterUniversity of Electronic Science and TechnologyChengduChina

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