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A hybrid system using PSO and data mining for determining the ranking of a new participant in Eurovision

Published: 12 July 2008 Publication History

Abstract

The intention of the present work is to apply data mining and PSO to propose the solution of a specific problem about society modelling. We analyze the voting behavior and ratings of judges in a popular song contest held every year in Europe. The dataset makes it possible to analyze the determinants of success, and gives a rare opportunity to run a direct test of vote trading from logrolling. We show that they are rather driven by linguistic and cultural proximities between singers and voting countries. With this information it is possible to predict the final rank of a new country in the contest.

References

[1]
D. Fenn, O. Suleman, J. Efstathiou, N.F. Johnson. Eurovision Make Its Mind Up? Connections, cliques, and compability between countries in The Eurovision Song Contest. Physica A: Statistical Mechanics and its Applications, 2005.
[2]
G. Yair. Unite Unite Europe: The political and cultural structures of Europe as reflected in the Eurovision Song Contest. Social Networks, Vol. 17 (2), pp. 147--161, 1995.
[3]
V. Ginsburgh, A. Noury. Cultural Voting: The Eurovision Song Contest. http://ssrn.com/abstract=884379, 2005.
[4]
H. Moser. Twelve points Grand Prix Eurovision, Analyse einer Fankultur. Verlag Pesstalozzianum, 1999.
[5]
A.E. Munoz, A. Hernández, E.R. Villa. Constrained optimization via particle evolutionary swarm optimization algorithm (PESO). Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 209--216, Washington DC, USA, 2005.

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  • (2014)Evolutionary clustering algorithm for community detection using graph-based information2014 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2014.6900555(930-937)Online publication date: Jul-2014

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  1. A hybrid system using PSO and data mining for determining the ranking of a new participant in Eurovision

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    cover image ACM Conferences
    GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation
    July 2008
    1814 pages
    ISBN:9781605581309
    DOI:10.1145/1389095
    • Conference Chair:
    • Conor Ryan,
    • Editor:
    • Maarten Keijzer
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 12 July 2008

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    Author Tags

    1. PSO
    2. data mining
    3. social modeling

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    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    • (2014)Evolutionary clustering algorithm for community detection using graph-based information2014 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2014.6900555(930-937)Online publication date: Jul-2014

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