Sequential pattern mining is the process of mining
relationships amid elements. The relationships like causal,
blocking etc leads to analogue of various kinds of sequential
patterns. Association rule mining allows to abundance
associations between elements without the concrete notion of
time. Sequential pattern mining incorporates temporal ordering
into the mining process. This allows accretion of knowledge of
associations among elements in the course of time. This paper is
intended to give a brief insight into the landmark research that
has brought the area of sequential pattern mining into limelight.
Gurram Sunitha : has completed B.E. in
Electronics & Communications Engineering
from Gulbarga University in 1999 and
M.Tech in Computer Sciences from JNT
University, Anantapur in 2005. Currently
she is pursuing Ph.D. in Computer Science
and Engineering at S.V.University, Tirupati.
Her research interests include Data Mining,
Automata Theory and Database Systems.
Dr. A. Rama Mohan Reddy : received his
B.Tech. degree from JNT University,
Anantapur in 1986, M. Tech degree in
Computer Science from NIT, Warangal in
2000 and Ph.D. in Computer Science and
Engineering in 2008 from S. V. University,
Tirupathi. He is presently working as
Professor in Department of Computer
Science and Engineering, S. V. University
College of Engineering, Tirupathi, A.P. India. His research interests
include Software Architecture, Software Engineering and Data
Mining. He is life member of ISTE and IE.
Data Mining
Frequent Patterns
Sequential
Patterns
Transactional Databases
Sequence Databases
In this paper, the problem of sequential pattern mining is
underlined. Algorithms and techniques for the purpose of
extracting knowledge in the form of sequential patterns
have been discussed. An effort is made to debrief the
process of focused mining and incremental mining.
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