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What is Association Rule Mining

Business Management and Communication Perspectives in Industry 4.0
It is used for searching interesting relationships among items in a given data set.
Published in Chapter:
Application of Utility Mining in Supply Chain Management
Reshu Agarwal (G. L. Bajaj Institute of Technology and Management, India)
Copyright: © 2020 |Pages: 17
DOI: 10.4018/978-1-5225-9416-1.ch012
Abstract
Supply chain management (SCM) assumes an exceptionally indispensable part in overseeing and sorting out big business forms, expanding operational productivity of the association. Inventory management is turning into a need to enhance the establishment and framework inside social orders which thusly builds the financial development. The examination discoveries demonstrate that despite the fact that it appears that SCM gives numerous administrations, it has a few issues as well including poor stock administration, bullwhip impact, high cost of coordination, innovation use, and lacking interest in IT. To beat issues of SCM, there is need of an enhanced sales forecasting model that will build the reliable and efficient forecasting results. An enhanced sales forecasting model is presented in this chapter.
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Recent Trends in Spatial Data Mining and Its Challenges
It is a method of discovering interesting relationship among a set of items or objects in a relational database, transactional database and other information repositories.
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An Approach for Estimating the Opportunity Cost Using Temporal Association Rule Mining and Clustering
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Data Mining for Business Analytics in Retail
The process of extracting association rules of the form X?Y from a data set. Association rule X?Y indicates that if X occurs in a record in the data set, then Y is likely to appear in the same record
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Efficient Ordering Policy for Imperfect Quality Items Using Association Rule Mining
Searching interesting relationships among items in a given data set.
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Discovering Personalized Novel Knowledge from Text
Mining algorithms which identify rules which are highly associated with each other.
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Fuzzy Sequential Patterns for Quantitative Data Mining
It is the mining of rules showing attribute value conditions frequently occurring together in a given set of data.
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Introduction to Fuzzy Data Mining Methods
Aims to discover dependencies between attributes on the basis of frequent item sets extracted from the measured data.
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Understanding Shopping Behaviors With Category- and Brand-Level Market Basket Analysis
A technique in data mining to discover patterns that represent the relationship among items that frequently exist together in a data set.
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Analysis of Industrial and Household IoT Data Using Computationally Intelligent Algorithm
Association rule can be represented as A->B, where A & B are disjoint item sets. The association rule can be generated based on the value of support and confidence.
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