On the Use of Rough Set Theory for Mining Periodic Frequent Patterns

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Author(s)

Manjeet Samoliya 1,* Akhilesh Tiwari 1

1. Department of CSE & IT, Madhav Institute of Technology and Science, Gwalior (M.P), 474005, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2016.07.08

Received: 4 Sep. 2015 / Revised: 5 Jan. 2016 / Accepted: 29 Mar. 2016 / Published: 8 Jul. 2016

Index Terms

Association rule mining, frequent pattern, periodic pattern mining, rough sets, temporal database

Abstract

This paper presents a new Apriori based approach for mining periodic frequent patterns from the temporal database. The proposed approach utilizes the concept of rough set theory for obtaining reduced representation of the initially considered temporal database. In order to consider only the relevant items for analyzing seasonal effects, a decision attribute festival has been considered. It has been observed that the proposed approach works fine for the analysis of the seasonal impact on buying behavior of customers. Considering the capability of approach for the analysis of seasonal profitability concern, decision making, and future marketing may use it for the important decision-making process for the uplifting of sell.

Cite This Paper

Manjeet Samoliya, Akhilesh Tiwari, "On the Use of Rough Set Theory for Mining Periodic Frequent Patterns", International Journal of Information Technology and Computer Science(IJITCS), Vol.8, No.7, pp.53-60, 2016. DOI:10.5815/ijitcs.2016.07.08

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