Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
Building Data Mining Applications for CRM
Building Data Mining Applications for CRM
Data mining of association structures to model consumer behaviour
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
CircleView: a new approach for visualizing time-related multidimensional data sets
Proceedings of the working conference on Advanced visual interfaces
A new collaborative system framework based on a multiple perspective approach: InteliTeam
Decision Support Systems - Special issue: Collaborative work and knowledge management
For effective facilities planning: layout optimization then simulation, or vice versa?
WSC '05 Proceedings of the 37th conference on Winter simulation
Ranking discovered rules from data mining with multiple criteria by data envelopment analysis
Expert Systems with Applications: An International Journal
Efficient mining of generalized association rules with non-uniform minimum support
Data & Knowledge Engineering
ICACTE '08 Proceedings of the 2008 International Conference on Advanced Computer Theory and Engineering
Mining customer knowledge for direct selling and marketing
Expert Systems with Applications: An International Journal
A comparative study of dimensionality reduction techniques to enhance trace clustering performances
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
The success of retail business is influenced by its fast response and its ability in understanding consumers' behaviors. Analysis of transaction data is the key for taking advantage of these new opportunities, which enables supermarkets to understand and predict customer behavior, has become a crucial technique for effective decision-making and strategy formation. We propose a methodological framework for the use of the knowledge discovery process and its visualization to improve store layout. This study examines the layout strategy in relation to supermarket retail stores and assists managers in developing better layout for supermarkets. We use the buying association measure to create a category correlation matrix and we apply the multidimensional scale technique to display the set of products in the store space. This is a new approach to supermarket layout from industrial categories to consumption universes that is consumer-oriented store layout approach through a data mining approach. This framework is useful for both academia and retail industry. For industry professionals, it may be used to guide development of successful layout. Retailers can utilize the proposed model to dynamically improve their in-store conversion rate. As the empirical study, a practical application proceeded for Migros Turk, a leading Turkish retailing company.