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Survey on Constrained based Data Stream Mining

by Lini Susan Kurien, Sreekumar K, Minu Kk
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 16
Year of Publication: 2014
Authors: Lini Susan Kurien, Sreekumar K, Minu Kk

Lini Susan Kurien, Sreekumar K, Minu Kk . Survey on Constrained based Data Stream Mining. International Journal of Computer Applications. 107, 16 ( December 2014), 12-15. DOI=10.5120/18834-0348

@article{ 10.5120/18834-0348,
author = { Lini Susan Kurien, Sreekumar K, Minu Kk },
title = { Survey on Constrained based Data Stream Mining },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 16 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { },
doi = { 10.5120/18834-0348 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:41:12.769386+05:30
%A Lini Susan Kurien
%A Sreekumar K
%A Minu Kk
%T Survey on Constrained based Data Stream Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 16
%P 12-15
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

In most of the real time applications data may arrive as continuous ordered sequence of items, called Data streams. The main challenge in dealing with the Data Stream is its voluminous, complex and dynamically arriving stream of data. There are certain techniques to deal with data streams, in particular, finding the frequent or sequential patterns that occur repeatedly. These results retrieve huge number of patterns, which are hard to analyze and use them, also difficult to store these results and its intermediate results. The traditional pattern mining techniques fail to give the relevant details to the user. In order to obtain that, some constraint based mining techniques, which acts as a filter to the large result set retrieved from traditional pattern mining techniques. This paper investigates different data stream mining techniques and constrained based stream mining techniques from which the user gets the required information from the data stream.

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Index Terms

Computer Science
Information Sciences


Data stream mining Frequent Pattern Mining Constraints Sequential Pattern Mining.