SPM: Study of Different Techniques of Sequential Pattern Mining

Authors

  • Sujit R. Wakchaure Department of Computer Science & Engineering, Dr. A. P. J. Abdul Kalam University, Indore(M.P.) 452010
  • Rajeev G. Vishwakarma Department of Computer Science & Engineering, Dr. A. P. J. Abdul Kalam University, Indore (M.P.) 452010

Keywords:

Sequential Pattern Mining, Apriori Technique, Frequent pattern growth technique

Abstract

An essential part of data mining is the process of finding unexpected and significant patterns hidden within databases. In the past several years, one trend that has emerged in the field of data mining is the development of algorithms for the purpose of locating patterns in sequential data. Sequential Pattern Mining (SPM) is one of the most well-known data mining activities that can be performed on sequences. Finding relevant subsequence’s within a set of sequences is the goal of this process. The interestingness of a subsequence can be evaluated based on a number of factors, such as how frequently it occurs, how long it lasts, and how much profit it brings in. Because data is encoded as sequences in many domains, including genomics, e-learning, market basket analysis, information extraction, and webpage click-stream assessment, sequential pattern mining has numerous real - world applications. This is because sequences are used to organise the data in these fields. This paper provides a comprehensive review of recent research on sequential pattern mining and its various applications. The purpose of this article is to evaluate recent developments in sequential pattern mining as well as provide an overview to the field of sequential pattern mining. This article offers a structured study on SPM as well as an analysis of the approaches that are used by SPM. In addition to this, it discusses the concerns, research issues, and future developments that are associated with sequential pattern mining.

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Classification of Prefix Growth based mining Technique

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Published

16.04.2023

How to Cite

Wakchaure, S. R. ., & Vishwakarma, R. G. . (2023). SPM: Study of Different Techniques of Sequential Pattern Mining. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 442–457. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/2806