Journal of Systems Science and Complexity

, Volume 26, Issue 1, pp 117–136 | Cite as

Complex concept lattices for simulating human prediction in sport

  • Gonzalo A. Aranda-Corral
  • Joaquín Borrego-Díaz
  • Juan Galán-Páez


In order to address the study of complex systems, the detection of patterns in their dynamics could play a key role in understanding their evolution. In particular, global patterns are required to detect emergent concepts and trends, some of them of a qualitative nature. Formal concept analysis (FCA) is a theory whose goal is to discover and extract knowledge from qualitative data (organized in concept lattices). In complex environments, such as sport competitions, the large amount of information currently available turns concept lattices into complex networks. The authors analyze how to apply FCA reasoning in order to increase confidence in sports predictions by means of detecting regularities from data through the management of intuitive and natural attributes extracted from publicly available information. The complexity of concept lattices -considered as networks with complex topological structure- is analyzed. It is applied to building a knowledge based system for confidence-based reasoning, which simulates how humans tend to avoid the complexity of concept networks by means of bounded reasoning skills.

Key words

Bounded rationality complex networks formal concept analysis sport forecasting 


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Copyright information

© Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gonzalo A. Aranda-Corral
    • 1
  • Joaquín Borrego-Díaz
    • 2
  • Juan Galán-Páez
    • 2
  1. 1.Department of Information TechnologyUniversidad de HuelvaPalos de La FronteraSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversidad de SevillaSevillaSpain

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