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Mining Maximal Sparse Interval

by Naba Jyoti Sarmah, Anjana Kakoti Mahanta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 5
Year of Publication: 2012
Authors: Naba Jyoti Sarmah, Anjana Kakoti Mahanta
10.5120/9281-3472

Naba Jyoti Sarmah, Anjana Kakoti Mahanta . Mining Maximal Sparse Interval. International Journal of Computer Applications. 58, 5 ( November 2012), 31-34. DOI=10.5120/9281-3472

@article{ 10.5120/9281-3472,
author = { Naba Jyoti Sarmah, Anjana Kakoti Mahanta },
title = { Mining Maximal Sparse Interval },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 5 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number5/9281-3472/ },
doi = { 10.5120/9281-3472 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:42.087534+05:30
%A Naba Jyoti Sarmah
%A Anjana Kakoti Mahanta
%T Mining Maximal Sparse Interval
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 5
%P 31-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Intervals are found in many real life applications such as web uses; stock market information; patient disease records; records maintained for occurrences of events, either man made or natural etc. Mining frequent intervals from such data allow us to group the transactions with similar behavior. Similar to frequent intervals, mining sparse intervals are also important. In this paper we define the notion of sparse and maximal sparse interval and also propose an algorithm for mining maximal sparse intervals. Computer programs were written and experimented on real life data set and results obtained have been reported. The correctness of the algorithm has also been proved.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Interval Data Mining Maximal Sparse Interval

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