Mining Sequential Patterns from Super Market Datasets

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-30 Number-4
Year of Publication : 2015
Authors : Fokrul Alom Mazarbhuiya
  10.14445/22312803/IJCTT-V30P136

MLA

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.