Fakultät für Mathematik und Naturwissenschaften

Wie erkennt Shazam ein Lied so schnell?

  1. A. Wang, The Shazam music recognition service, Communications of the ACM 49(8) (2006), 44-48.
  2. M.A. Casey, R. Veltkamp, M. Goto, M. Leman, C. Rhodes, M. Slaney, Content-based music information retrieval: Current directions and future challenges, Proceedings of the IEEE, 96(4) (2008), 668-696.
  3. M. Kaminskas, F. Ricci, Contextual music information retrieval and recommendation: State of the art and challenges, Computer Science Review, 6(2-3) (2012), 89-119.
  4. F. Zalkow, J. Brandner, M. Müller, Efficient Retrieval of Music Recordings Using Graph-Based Index Structures, Signals 2(2) (2021), 336-352.
  5. K. Noack (Matheretter), Wie funktioniert Shazam?

Wie fair ist der Gesangswettbewerb?

  1. L. Spierdijk, M. Vellekoop, The structure of bias in peer voting systems: lessons from the Eurovision Song Contest, Empirical Economics 36(2) (2009), 403-425.
  2. D. Fenn, O. Suleman, J. Efstathiou und N.F. Johnson, How does Europe make its mind up? Connections, cliques, and compatibility between countries in the Eurovision Song Contest, Physica A: Statistical Mechanics and its Applications 360 (2006), 576-598.
  3. G. Bello-Orgaz, H.D. Menéndez, D. Camacho, Adaptive k-means algorithm for overlapped graph clustering, International Journal of Neural Systems, 22(05) (2012), 1250018.
  4. G. Bello-Orgaz, D. Camacho, Evolutionary clustering algorithm for community detection using graph-based information, In: 2014 IEEE congress on evolutionary computation (CEC), 2014. pp. 930-937.
  5. Derek Gatherer, Birth of a Meme: the Origin and Evolution of Collusive Voting Patterns in the Eurovision Song Contest, Journal of Memetics - Evolutionary Models of Information Transmission, 8.
  6. D. Gatherer, Comparison of Eurovision Song Contest simulation with actual results reveals shifting patterns of collusive voting alliances, Journal of Artificial Societies and Social Simulation, 9(2) (2006).
  7. A. Dekker, The Eurovision Song Contest as a ‘friendship’network, Connections, 27(3) (2007), 53-58.
  8. D. García, D. Tanase, Measuring cultural dynamics through the Eurovision song contest, Advances in Complex Systems, 16(08) (2013), 1350037.
  9. T. Highfield, S. Harrington, A. Bruns, Twitter as a technology for audiencing and fandom: The #Eurovision phenomenon, Information, Communication & Society, 16(3) (2013), 315-339.
  10. R. Tobin (ed.), A song for Europe: Popular music and politics in the Eurovision Song Contest, Routledge, 2017.
  11. V. Ginsburgh, A.G. Noury, The Eurovision song contest. Is voting political or cultural?, European Journal of Political Economy, 24(1) (2008), 41-52.
  12. A.L. Barabâsi, H. Jeong, Z. Néda, E. Ravasz, A. Schubert, T. Vicsek, Evolution of the social network of scientific collaborations, Physica A: Statistical Mechanics and its Applications, 311(3-4) (2002), 590-614.
  13. C. Cotta, A.M. Mora, J.J. Merelo, C. Merelo-Molina, A network analysis of the 2010 FIFA world cup champion team play, Journal of Systems Science and Complexity, 26(1) (2013), 21-42.
  14. J.Heer, D. Boyd, vizster - visualizing online social networks, Berkeley, 2005.
  15. SocNetV: Social Network Analysis and Visualization Software.
  16. A. Bartel, M. Ehrhardt, ESC2010 Datenfile für SocNetV

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