A Survey on Different Approaches for Sequential Pattern Mining

Authors(3) :-Bhargav Shroff, Bakul Panchal, Manmitsinh Zala

In data mining, mining sequential pattern from very huge amount of database is very useful in many applications. Most of sequential pattern mining algorithms work on static data means the database should not change. But the databases in today’s real world application do not have static data, they are incremental databases. New transactions are added at some intervals of time. For updated database, the algorithm needs to be executed again for whole sequence database. So those approaches are not appropriate to use, for that algorithm with incremental approach should be modelled and used. This paper analysis existing approaches for finding sequential pattern mining, and the survey would be helpful in forming a new model or improving some existing approach to handle incremented database & obtain sequential patterns out of them.

Authors and Affiliations

Bhargav Shroff
Information Technology Department, L. D. Engineering College, Ahmedabad, Gujarat, India
Bakul Panchal
Information Technology Department, L. D. Engineering College, Ahmedabad, Gujarat, India
Manmitsinh Zala
Information Technology Department, Alpha college of engineering and Technology, Ahmedabad, Gujarat, India

BLSPM, Incremental approach, IncSpan, PrefixSpan, Sequential Pattern mining.

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  4. “IncSpan: Incremental Mining of Sequential Patterns in Large Database”, Hong Cheng, Xifeng Yan, in ACM
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Publication Details

Published in : Volume 1 | Issue 6 | November-December 2015
Date of Publication : 2015-12-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 131-134
Manuscript Number : IJSRSET151620
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Bhargav Shroff, Bakul Panchal, Manmitsinh Zala, " A Survey on Different Approaches for Sequential Pattern Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.131-134, November-December-2015.
Journal URL : http://ijsrset.com/IJSRSET151620

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