Applying Data Mining Techniques For Store Layout of A Super Market

Authors(2) :-S. Seshadri, Prasad Babu

The said framework is intended to discover the most incessant blends of things. It depends on building up a proficient calculation that outflanks the best accessible successive example calculations on various run of the mill informational indexes. This will help in advertising and deals. The strategy can be utilized to reveal fascinating strategically pitches and related items. The calculations from affiliation mining have been actualized and afterward best blend strategy is used to discover all the more intriguing outcomes. The examiner at that point can play out the information mining and extraction lastly finish up the outcome and settle on proper choice. Market container examination is a vital part of logical framework in retail associations to decide the arrangement of products, planning deals advancements for various fragments of clients to enhance consumer loyalty and thus the benefit of the general store. These issues for a driving general store are tended to here utilizing continuous itemset mining. The regular itemsets are mined from the advertise crate database utilizing the productive Apriori calculation and afterward the affiliation rules are created.

Authors and Affiliations

S. Seshadri
Student,Department of MCA, RCR Institute of Management, Tirupati, India
Prasad Babu
Assistant Professor, Department of MCA, RCR Institute of Management, Tirupati, India

Data Mining, Decision Support Systems, Association Rules, Market Basket Analysis, Apriori Algorithm , Store Layout

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Publication Details

Published in : Volume 4 | Issue 2 | March-April 2018
Date of Publication : 2018-03-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 481-483
Manuscript Number : CSEIT184184
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S. Seshadri, Prasad Babu, "Applying Data Mining Techniques For Store Layout of A Super Market", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 2, pp.481-483, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT184184

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