Advertisement

Intelligent Music Recommendation System Based on Cloud Computing

  • Ki-Young Lee
  • Tae-Min Kwun
  • Myung-Jae Lim
  • Kyu-Ho Kim
  • Jeong-Lae Kim
  • Il-Hee Seo
Part of the Communications in Computer and Information Science book series (CCIS, volume 263)

Abstract

In this paper, intelligent music recommend system is proposed based on clouding computer. User- selected music is classified to similar tendency by algorithm of music genre classification, after total of 12 musical feature extraction on cloud. This system classified using Thayer’s model of mood and music was classified again suitable for current weather conditions. So, we suggested to music recommend system based on cloud computing system recommend for user and verified through simulation. The results of performance evaluation show that the proposed system can efficiently support weather condition and season information.

Keywords

Music Recommend System Feature Extract Cloud Computing Thayer’s Model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Platt, J.C., Burges, C., Swenson, S., Weare, C., Zheng, A.: Learning a Gaussian Process Prior for Automatically Generating Music Playlist. In: Proc. NIPS, vol. 14, pp. 1425–1423 (2002)Google Scholar
  2. 2.
    Tzanetakis, G., Cook, P.: Musical Genre Classification of Audio Signals Speech and Audio Processing. IEEE Transactions 10(5), 293–302 (2002)Google Scholar
  3. 3.
    Li, T., Ogihara, M., Li, Q.: A Comparative Study on Content-Based Music Genre Classification. In: Proc. of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 282–289 (2003)Google Scholar
  4. 4.
    Rabiner, L.R.: Fundamentals of Speech Recognition. Prentice Hall (1993)Google Scholar
  5. 5.
    Thayer, R.E.: The Biopsychology of Mood and Arousal. Oxford University Press (1989)Google Scholar
  6. 6.
    Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)zbMATHGoogle Scholar
  7. 7.
    Extracting Features from Audio Files, http://jmir.sourceforge.net

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ki-Young Lee
    • 1
  • Tae-Min Kwun
    • 1
  • Myung-Jae Lim
    • 1
  • Kyu-Ho Kim
    • 1
  • Jeong-Lae Kim
    • 2
  • Il-Hee Seo
    • 1
  1. 1.Department of Medical IT and MarketingEulji UniversitySeongnam-siKorea
  2. 2.Department of Biomedical EngineeringEulji UniversityKorea

Personalised recommendations