International Journal of Computer
Trends and Technology

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Volume 30 | Number 1 | Year 2015 | Article Id. IJCTT-V30P136 | DOI : https://doi.org/10.14445/22312803/IJCTT-V30P136

Mining Sequential Patterns from Super Market Datasets

Fokrul Alom Mazarbhuiya

Citation :

Fokrul Alom Mazarbhuiya, "Mining Sequential Patterns from Super Market Datasets," International Journal of Computer Trends and Technology (IJCTT), vol. 30, no. 1, pp. 206-212, 2015. Crossref, https://doi.org/10.14445/22312803/IJCTT-V30P136

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.

Keywords

Locally frequent itemsets, Temporal data mining, Frequent sequence, Maximal frequent sequence.

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