Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/8760
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | SWINNEN, Gilbert | - |
dc.contributor.advisor | VANHOOF, Koen | - |
dc.contributor.author | BRIJS, Tom | - |
dc.date.accessioned | 2008-12-03T19:16:12Z | - |
dc.date.available | 2008-12-03T19:16:12Z | - |
dc.date.issued | 2002 | - |
dc.identifier.uri | http://hdl.handle.net/1942/8760 | - |
dc.description.abstract | Market basket analysis is a generic term for methodologies that study the composition of a basket of products (i.e. a shopping basket) purchased by a household during a single shopping trip. The idea is that market baskets reflect interdependencies between products or purchases made in different product categories, and that these interdependencies can be useful to support retail marketing decisions. Recently, a number of advances in data mining (association rules) and statistics (mixture models) offer new opportunities to analyse such data. In this dissertation, the focus is therefore on the development and application of such techniques for two specific problems where product/category interdependencies play an important role, i.e. in product selection and in behaviour-based customer segmentation. ... | - |
dc.publisher | UHasselt Diepenbeek | - |
dc.title | Retail market basket analysis: a quantitative modelling approach | - |
dc.type | Theses and Dissertations | - |
local.bibliographicCitation.jcat | T1 | - |
local.type.specified | Phd thesis | - |
dc.bibliographicCitation.oldjcat | D1 | - |
item.accessRights | Open Access | - |
item.contributor | BRIJS, Tom | - |
item.fullcitation | BRIJS, Tom (2002) Retail market basket analysis: a quantitative modelling approach. | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | PhD theses Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
TomBrijs.pdf | 2.83 MB | Adobe PDF | View/Open |
Page view(s)
116
checked on Nov 7, 2023
Download(s)
180
checked on Nov 7, 2023
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.