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Comparative Study of Various Sequential Pattern Mining Algorithms

by Nidhi Grover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 17
Year of Publication: 2014
Authors: Nidhi Grover

Nidhi Grover . Comparative Study of Various Sequential Pattern Mining Algorithms. International Journal of Computer Applications. 90, 17 ( March 2014), 36-41. DOI=10.5120/15815-4703

@article{ 10.5120/15815-4703,
author = { Nidhi Grover },
title = { Comparative Study of Various Sequential Pattern Mining Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 17 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { },
doi = { 10.5120/15815-4703 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:11:19.409422+05:30
%A Nidhi Grover
%T Comparative Study of Various Sequential Pattern Mining Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 17
%P 36-41
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

In Sequential pattern mining represents an important class of data mining problems with wide range of applications. It is one of the very challenging problems because it deals with the careful scanning of a combinatorially large number of possible subsequence patterns. Broadly sequential pattern ming algorithms can be classified into three types namely Apriori based approaches, Pattern growth algorithms and Early pruning algorithms. These algorithms have further classification and extensions. Detailed explanation of each algorithm along with its important features, pseudo code, advantages and disadvantages is given in the subsequent sections of the paper. At the end a comparative analysis of all the algorithms with their supporting features is given in the form of a table. This paper tries to enrich the knowledge and understanding of various approaches of sequential pattern mining.

  1. Manan Parikh, Bharat Chaudhari and Chetna Chand, A Comparative Study of Sequential Pattern Mining Algorithms, Volume 2, Issue 2, February 2013, International Journal of Application or Innovation in Engineering & Management (IJAIEM)
  2. Thabet Slimani, and Amor Lazzez, Sequential Mining: Patterns And Algorithms Analysis
  3. Jiawei Han • Hong Cheng • Dong Xin • Xifeng Yan, Frequent pattern mining: current status and future directions Received: 22 June 2006 / Accepted: 8 November 2006 / Published online: 27 January 2007 Springer Science+Business Media, LLC 2007
  4. Mohammed J. Zaki, SPADE: An Efficient Algorithm for Mining Frequent Sequences, Machine Learning, 42, 31–60, 2001 2001 Kluwer Academic Publishers. Manufactured in The Netherlands zaki@cs. rpi. edu
  5. NIZAR R. MABROUKEH and C. I. EZEIFE, A Taxonomy of Sequential Pattern Mining Algorithms. University of Windsor,
  6. Cláudia Antunes and Arlindo L. Oliveira Instituto Superior Técnico, Sequential Pattern Mining Algorithms: Trade-offs between Speed and Memory, INESC-ID, Department of Information Systems and Computer Science, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
  7. Rakesh Agrawal and Ramakrishnan Srikant, Mining Sequential Patterns, IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120
  8. Rakesh Agrawal Ramakrishnan Srikan, Fast Algorithms for Mining Association Rules, IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120
  9. Murat Ali Bay?r, Ismail H. Toroslu and Ahmet Co?ar, A Performance Comparison of Pattern Discovery Methods on Web Log Data ,Department of Computer Engineering Middle East Technical University
  10. Behzad Mortazavi-Asl ,Discovering And Mining User Web-Page Traversal Patterns , Simon Fraser University, 1999
  11. Jian Pei, Jiawei Han, Behzad Mortazavi-Asl, Jianyong Wang, Helen Pinto, Qiming Chen Umeshwar Dayal, and Mei-Chun Hsu, Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach, Ieee Transactions On Knowledge And Data Engineering, Vol. 16, No. 10, October 2004
  12. J. Han, J. Pei, B. Mortazavi-Asl, Q. Chen, U. Dayal, and M. -C. Hsu, "FreeSpan: Frequent Pattern-Projected Sequential Pattern Mining," Proc. 2000 ACM SIGKDD Int'l Conf. Knowledge Discovery in Databases (KDD '00), pp. 355-359, Aug. 2000.
  13. J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M. -C. Hsu, "PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth," Proc. 2001 Int'l Conf. Data Eng. (ICDE '01), pp. 215-224, Apr. 2001.
Index Terms

Computer Science
Information Sciences


Basic Apriori GSP SPADE PrefixSpan FreeSpan LAPIN Early pruning.