Application and Analysis of Retail Inventory Using Data Mining Techniques

MD. Imtiaz Uddin; Tanvir Ahmed; A.H.M Saiful Islam; Redoyan Raz

Application and Analysis of Retail Inventory Using Data Mining Techniques

MD. Imtiaz Uddin *

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Tanvir Ahmed

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A.H.M Saiful Islam

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Redoyan Raz

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Application and Analysis of Retail Inventory Using Data Mining Techniques

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Abstract

Data mining is one of the most essential tools for gathering information from different datasets in almost all recent industries. In this 21st-century, data mining gained attention because of its significance in decision making, and it has become a key component in various industries such as retail. Inventory management requires pre-planned goals and attention to detail, and prioritizing items that require less attention can be a waste of time and resources. Learning indications about customers’ shopping patterns by showing associations among various provides significant value in managing retail inventory. In the present research paper, popular data mining techniques have been applied and analyzed for multi-item inventory management in retail sales stores to show how data mining techniques can optimize and organize the retail inventory.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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How to Cite This Article

MD. Imtiaz Uddin, Tanvir Ahmed, A.H.M Saiful Islam, Redoyan Raz. 2020. "Application and Analysis of Retail Inventory Using Data Mining Techniques". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 20 (GJCST Volume 20 Issue G2).

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GJCST Volume 20 Issue G2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-G Classification H.2.8

Submission ReceivedDecember 15, 2019
Peer Review Double Blind
Handling Editor
Accepted January 5, 2020
Published January 15, 2020

Version of record

v1.2

Issue date

March 30, 2020

Language

English

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