Clustering of Locally Frequent Patterns over Fuzzy Temporal Datasets
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.
Abstract -
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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Keywords
Data mining, Clustering, Temporal
patterns, Locally frequent itemset, Set
superimposition, Fuzzy time-interval.