An Efficient Implementation of an Algorithm for Mining Locally Frequent Patterns
Fokrul Alom Mazarbhuiya
Mining patterns from large dataset is an interested data mining problem. Many methods have been developed for this purpose till today. Most of the methods considered the time attributes as one of the normal attribute. However taking the time attribute into account separately the patterns can be extracted which cannot be extracted by normal methods. These patterns are termed as temporal patterns A couple of works have already been done in mining temporal patterns. A nice algorithm for mining locally frequent patterns from temporal datasets is proposed by Anjana et al. In this article, we propose a hash-tree based implementation of the algorithm. We also established the fact that the hash-tree based outperforms others.
Data Mining, Frequent patterns, Temporal patterns, Locally frequent patterns.
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[Fokrul Alom Mazarbhuiya (2016) An Efficient Implementation of an Algorithm for Mining Locally Frequent Patterns IJIREM Vol-3 Issue-1 Page No-55-58] (ISSN 2350 - 0557). www.ijirem.org
Fokrul Alom Mazarbhuiya
College of Computer Science & IT, Albaha University, Albaha, KSA firstname.lastname@example.org