Gilbert Swinnen

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Koen Vanhoof19
Tom Brijs15
Geert Wets13
Rakesh Agrawal10
Ramakrishnan Srikant10
20Koen Vanhoof
18Tom Brijs
16Geert Wets
7Ada Wai-Chee Fu
7Ke Wang

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1999
2017

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Using Association Rules for Product Assortment Decisions: A Case Study
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers. Moreover, recent work indicates that the discovery of interesting rules can in fact only be addressed within a microeconomic framework. This study integrates the discovery of… (More)
A Framework for Self Adaptive Websites: Tactical versus Strategic Changes
In the contemporary information society where the Internet performs a leading role, and the competition is just one mouse-click away, it is very important to communicate your message to the Website visitors in an optimal way. When creating a Website, the designer meticulously creates the look and feel of the site, designs the structure of the information,… (More)
A Data Mining Framework for Optimal Product Selection in Retail Supermarket Data: The Generalized PROFSET Model
In recent years, data mining researchers have developed efficient association rule algorithms for retail market basket analysis. Still, retailers often complain about how to adopt association rules to optimize concrete retail marketing-mix decisions. It is in this context that, in a previous paper, the authors have introduced a product selection model… (More)
Tuning the Multivariate Poisson Mixture Model for Clustering Supermarket Shoppers
This paper describes a multivariate Poisson mixture model for clustering supermarket shoppers based on their purchase frequency in a set of product categories. The multivariate nature of the model accounts for cross-selling effects that may exist between the purchases made in different product categories. However, because of computational difficulties, most… (More)
Building an Association Rules Framework to Improve Product Assortment Decisions
It has been claimed that the discovery of association rules is well suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers. However today, one disadvantage of associations discovery is that there is no provision for taking into account the business value of an association. Therefore, recent work… (More)
Comparing complete and partial classification for identifying customers at risk
This paper evaluates complete versus partial classification for the problem of identifying customers at risk. We define customers at risk as customers reporting overall satisfaction, but these customers also possess characteristics that are strongly associated with dissatisfied customers. This definition enables two viable methodological approaches for… (More)
The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning
Direct mail is a typical example for response modeling to be used. In order to decide which people will receive the mailing, the potential customers are divided into two groups or classes (buyers and non-buyers) and a response model is created. Since the improvement of response modeling is the purpose of this paper, we suggest a combined approach of… (More)
Using Association Rules for Product Assortment Decisions in Automated Convenience Stores
Association rules is a recent data mining technique to discover affinities, in large transaction databases, between items frequently purchased together. It has been claimed that the discovery of frequent sets of items is well suited for applications of market basket analysis to discover regularities in the purchase behaviour of customers. In this study, we… (More)