Mining Sequential Patterns from Super Market Datasets
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-30 Number-4 |
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| Year of Publication : 2015 | ||
| Authors : Fokrul Alom Mazarbhuiya | ||
| DOI : 10.14445/22312803/IJCTT-V30P136 |
Fokrul Alom Mazarbhuiya "Mining Sequential Patterns from Super Market Datasets". International Journal of Computer Trends and Technology (IJCTT) V30(4):206-212, December 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Mining sequential patterns is an
important data-mining problem and it has many
application domains such as Supermarket Medical
science, signal processing and speech analysis. The
problem involves mining causal relationship
between events. Mining sequence from supermarket
is an interesting data mining problem. In this paper,
we propose a method of mining such patterns. Our
approach is completely different from others in the
sense that we are interested to find inter-item sets
patterns however in other cases patterns are intertransactions.
In our case we first find all frequent
itemsets where each frequent itemsets is associated
with the lists of time intervals in which it is frequent.
Sequential patterns can be generated using the lists
of time intervals associated with frequent itemsets.
The efficacy of the method is established using
experimental results.
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Keywords
Locally frequent itemsets, Temporal data
mining, Frequent sequence, Maximal frequent
sequence.