Research on Rough Set Theory-Based Customer Division

Gui Juan Song; Xin Cao; Xin Yue Wang

doi:10.4028/www.scientific.net/AMR.989-994.1536

Paper Titles

Research on Customers Churn Prediction Model Based on Logistic
p.1517

Site Selection of Customer Operation Center for Pull and Drag Transportation Based on the Analytic Hierarchy Process
p.1522

Research on the Layout of Integrated Freight Hub Based on Two-Stage Model
p.1526

The Optimization of Logistics and Distribution
p.1532

Research on Rough Set Theory-Based Customer Division
p.1536

A K-Nearest-Neighbour Based Classifier for Securities Text Categorization
p.1541

Research of Intelligent Warehouse Layout Base on Genetic Algorithm and Dynamic Programming
p.1547

A Generalized Attributes Significance Measure Method
p.1551

A Fusion Method of Point-Cloud Based on Parallel Estimation of Distribution Algorithm
p.1555

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Research on Rough Set Theory-Based Customer Division

Abstract:

The main idea of rough set theory is to extract decision rules by attribute reduction and value reduction in the premises of keeping the ability of classification. This paper presents the design of model for customer division based on rough set, and uses algorithms for attribute reduction and rule extraction in rough set to analyze the customer of supermarket. This paper also introduces how to achieve the minimum result of attribute reduction and decision-making via decision-making report, winkling redundant attribute and over-rule of decision.