Progress in Artificial Intelligence

, Volume 5, Issue 3, pp 165–170 | Cite as

Pattern mining: current status and emerging topics

  • Jose Maria LunaEmail author
Regular Paper


The extraction of patterns of interest and associations between them have been a major research topic since its definition at the beginning of the nineties. Abundant research studies have been dedicated to this field, providing overwhelming progresses in both efficiency and scalability, and extracting patterns from different data structures and domains. Since pattern mining is the keystone of data analysis, many application fields and, specially, numerous researchers have focused their attention on the discovery of patterns and associations that describe and represent any type of homogeneity and regularity in data. The growing scope of applications of pattern mining has deep impact on pattern mining models based on data domains, data dimensionality, data comprehensibility and data flexibility. All of these provides new and challenging research issues that need to be solved, broaden new research lines and leaving early pattern mining problems that can be considered as solved already.


Pattern mining Data comprehensibility Data dimensionality Data flexibility 



This work was supported by the Spanish Ministry of Economy and Competitiveness under the Project TIN2014-55252-P, and FEDER funds.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Computer Science and Numerical AnalysisUniversity of CordobaCordobaSpain

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