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An Efficient Algorithm for Mining Maximal Sparse Interval from Interval Dataset
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 107 - Number 16
Year of Publication: 2014
|
10.5120/18838-0374 |
Naba Jyoti Sarmah and Anjana Kakoti Mahanta. Article: An Efficient Algorithm for Mining Maximal Sparse Interval from Interval Dataset. International Journal of Computer Applications 107(16):28-32, December 2014. Full text available. BibTeX
@article{key:article,
author = {Naba Jyoti Sarmah and Anjana Kakoti Mahanta},
title = {Article: An Efficient Algorithm for Mining Maximal Sparse Interval from Interval Dataset},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {107},
number = {16},
pages = {28-32},
month = {December},
note = {Full text available}
}
Abstract
Many real world data are closely associated with intervals. Mining frequent intervals from such data allows us to group those data depending on some similarity. A few numbers of data mining approaches have been developed to discover frequent intervals from interval datasets. Here we present a complementary approach in which we search for sparse intervals in data. We present an efficient algorithm with a worst case time complexity of O(n log n) for mining maximal sparse intervals.
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