Discovery of Periodic Rare Correlated Patterns from Static Database

Upadhya K. Jyothi, B. Dinesh Rao, M. Geetha, Harsh Kamlesh Vora

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Finding the associations among the itemsets and discovering the unknown or unexpected behavior are the major tasks of rare pattern mining. The support measure has the main contribution during the discovery of low support patterns. As the association of low support patterns may generate a bundle of spurious patterns, other measures are used to find the correlation between the itemsets. A generalization of frequent pattern mining called periodic frequent pattern mining (PFPM) is emerged as a promising field, focusing on the occurrence behavior of frequent patterns. On the contrary, the shape of occurrence in the case of rare pattern mining is not much studied. In this paper, a single scan algorithm called PRCPMiner is proposed to study the shape of occurrence of rare patterns. The proposed algorithm discovers periodic rare correlated patterns using different thresholds with respect to support, bond, and periodicity measures. The research shows the influence of these thresholds on the runtime performance for various datasets.

Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Advance Computing and Intelligent Engineering - ICACIE 2021
EditorsBibudhendu Pati, Chhabi Rani Panigrahi, Prasant Mohapatra, Kuan-Ching Li
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9789811922244
Publication statusPublished - 2023
Event6th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2021 - Bhubaneswar, India
Duration: 23-12-202124-12-2021

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference6th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


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