Genetic Algorithm for Burst Detection and Activity Tracking in Event Streams

  • Lourdes Araujo
  • José A. Cuesta
  • Juan J. Merelo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


We introduce a new model for detection and tracking of bursts of events in a discrete temporal sequence, its only requirement being that the time scale of events is long enough to make a discrete time description meaningful. A model for the occurrence of events using with Poisson distributions is proposed, which, applying Bayesian inference transforms into the well-known Potts model of Statistical Physics, with Potts variables equal to the Poisson parameters (frequencies of events). The problem then is to find the configuration that minimizes the Potts energy, what is achieved by applying an evolutionary algorithm specially designed to incorporate the heuristics of the model. We use it to analyze data streams of very different nature, such as seismic events and weblog comments that mention a particular word. Results are compared to those of a standard dynamic programming algorithm (Viterbi) which finds the exact solution to this minimization problem. We find that, whenever both methods reach a solution, they are very similar, but the evolutionary algorithm outperforms Viterbi’s algorithm in running time by several orders of magnitude, yielding a good solution even in cases where Viterbi takes months to complete the search.


Genetic Algorithm Evolutionary Algorithm Bayesian Inference Crossover Rate Event Stream 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lourdes Araujo
    • 1
  • José A. Cuesta
    • 2
  • Juan J. Merelo
    • 3
  1. 1.Departamento de Sistemas Informáticos y ProgramaciónUniversidad Complutense de MadridSpain
  2. 2.Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de MatemáticasUniversidad Carlos III de MadridSpain
  3. 3.Departamento de Arquitectura y Tecnología de ComputadoresUniversidad de GranadaSpain

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