An Integrated Framework for Relational and Hierarchical Mining of Frequent Closed Patterns

  • B. Pravin Kumar
  • V. Divakar
  • E. Vinoth
  • Radha SenthilKumar
Part of the Communications in Computer and Information Science book series (CCIS, volume 40)


This paper addresses an Integrated Framework for relational and hierarchical mining of Frequent Closed Pattern. Large data banks have created the necessity to formulate a system for effective retrieval of data patterns. The major issues that have to be dealt here are granularity of patterns, effectiveness of patterns and time taken for retrieval. Here we discuss Inter-related generalized self-organizing map (IGSOM) and relational attribute-oriented induction (RAOI), which are focused on pattern extraction along with CC-MINER, a hierarchical mining technique for exploring Frequent Closed Pattern from very dense data sets. We further provide implementation results for education data set and prostrate cancer data set.


IGSOM RAOI CC-Miner GSOM EAOI Cluster Pattern Frequent Closed Pattern 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • B. Pravin Kumar
    • 1
  • V. Divakar
    • 1
  • E. Vinoth
    • 1
  • Radha SenthilKumar
    • 1
  1. 1.Department of Information Technology, MIT CampusAnna UniversityChennaiIndia

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