Abstract
This paper presents a proposal of distribution’s estimated algorithm to the extraction of sequential patterns in a database which use a probabilistic model based on graphs which represent the relations among items that form a sequence. The model maps a probability among the items allowing them to adjust the model during the execution of the algorithm using the evolution process of EDA, optimizing the candidate’s generation of solution and extracting a group of sequential patterns optimized.
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Godinho, P.I.A., Meiguins, A.S.G., de Oliveira, R.C.L., Meiguins, B.S. (2010). An Estimation of Distribution Algorithms Applied to Sequence Pattern Mining. In: Sobh, T., Elleithy, K. (eds) Innovations in Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9112-3_102
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DOI: https://doi.org/10.1007/978-90-481-9112-3_102
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