Closed Frequent Pattern Mining Using Vertical Data Format: Depth First Approach

Authors(3) :-Md. Mohsin, Md. Rayhan Ahmed, Tanveer Ahmed

Frequent pattern finding plays an essential role in mining associations, correlations and many more interesting relationships among data. Discovery of such correlations among huge amount of business transaction records can help in many aspects of business-related decision-making processes like catalog design, cross-marketing and customer shopping behavior analysis. “Market Basket Analysis” is one of such applications. It involves analysis of customer buying patterns by finding associations between the different items that customers place in their shopping carts. The discovery of such associations can help retailers and analysts to develop marketing strategies by gaining insight into which items are frequently purchased together by customers leading to increased sales by helping retailers do selective marketing and design efficient store layout.

Authors and Affiliations

Md. Mohsin
Department of CSE, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
Md. Rayhan Ahmed
Department of CSE, Stamford University Bangladesh, Dhaka, Bangladesh
Tanveer Ahmed
Department of CSE, Stamford University Bangladesh, Dhaka, Bangladesh

Frequent Pattern Finding, Association Rules, Vertical Data Format, Closed Frequent Itemsets.

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2016
Date of Publication : 2016-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 230-238
Manuscript Number : IJSRSET162366
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Md. Mohsin, Md. Rayhan Ahmed, Tanveer Ahmed, " Closed Frequent Pattern Mining Using Vertical Data Format: Depth First Approach , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.230-238, May-June-2016.
Journal URL : http://ijsrset.com/IJSRSET162366

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