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Literature Review And Techniques Of Machine Learning Algorithm Used In Business Intelligence For Inventory Management

Authors: Sagar Malik*1 & Rashmi Jeswani*2;

Literature Review And Techniques Of Machine Learning Algorithm Used In Business Intelligence For Inventory Management

Abstract

In a global market that makes room for more competitors by the day, some companies are turning to AI and machine learning to try to gain an edge. Supply chain and inventory management is a domain that has missed some of the media limelight, but one where industry leaders have been hard at work developing new AI and machine learning technologies over the past decade. Many well-known companies are now using machine learning to optimize business processes in ways that might have been deemed science fiction 30 years ago, from customer service inquiries to planning for next month’s shelf supply based on satellite data. Supply chain and inventory management is primed to embody the concept of smart automation over the next five to 10 years. In this paper, we have investigated the research made till date and proposed a way to improve the inventory management so that it can benefit the customer as well as organizations.

Keywords

Marketing, Inventory Management, E-Commerce, Business Intelligence.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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