Clustering of Locally Frequent Patterns over Fuzzy Temporal Datasets
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2015 by IJCTT Journal|
|Year of Publication : 2015|
|Authors : Md Husamuddin, Fokrul Alom Mazarbhuiya|
|DOI : 10.14445/22312803/IJCTT-V28P124|
Md Husamuddin, Fokrul Alom Mazarbhuiya "Clustering of Locally Frequent Patterns over Fuzzy Temporal Datasets". International Journal of Computer Trends and Technology (IJCTT) V28(3):131-134, October 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
The study of discovering frequent patterns in a dataset is a well defined data mining problem. There are many approaches to resolve this problem including. Clustering is one of the common data mining approaches which is used for discovering data distribution and patterns in a dataset. Many algorithms have been proposed for finding clusters among frequent patterns itemsets. clustering fuzzy temporal data is an extension of temporal data mining. Here we try to find clusters among frequent itemsets based on fuzzy intervals of frequencies. In this paper, we propose a agglomerative hierarchical clustering algorithm to find clusters among the frequent itemsets obtained from fuzzy temporal data. The efficacy of the proposed method is established through experimentation on real datasets.
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Data mining, Clustering, Temporal patterns, Locally frequent itemset, Set superimposition, Fuzzy time-interval.