Mining value-based item packages - An integer programming approach

Traditional methods for discovering frequent patterns from large databases assume equal weights for all items of the database. In the real world, managerial decisions are based on economic values attached to the item sets. In this paper, we first introduce the concept of the value based frequent ite...

Full description

Bibliographic Details
Main Authors: Achuthan, Narasimaha, Gopalan, Raj, Rudra, Amit
Other Authors: Carbonell, J.
Format: Book Chapter
Published: Springer-Verlag 2006
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/44572
_version_ 1848757038913421312
author Achuthan, Narasimaha
Gopalan, Raj
Rudra, Amit
author2 Carbonell, J.
author_facet Carbonell, J.
Achuthan, Narasimaha
Gopalan, Raj
Rudra, Amit
author_sort Achuthan, Narasimaha
building Curtin Institutional Repository
collection Online Access
description Traditional methods for discovering frequent patterns from large databases assume equal weights for all items of the database. In the real world, managerial decisions are based on economic values attached to the item sets. In this paper, we first introduce the concept of the value based frequent item packages problems. Then we provide an integer linear programming (ILP) model for value based optimization problems in the context of transaction data. The specific problem discussed in this paper is to find an optimal set of item packages (or item sets making up the whole transaction) that returns maximum profit to the organization under some limited resources. The specification of this problem allows us to solve a number of practical decision problems, by applying the existing and new ILP solution techniques. The model has been implemented and tested with real life retail data. The test results are reported in the paper.
first_indexed 2025-11-14T09:21:45Z
format Book Chapter
id curtin-20.500.11937-44572
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:21:45Z
publishDate 2006
publisher Springer-Verlag
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-445722017-09-13T15:58:41Z Mining value-based item packages - An integer programming approach Achuthan, Narasimaha Gopalan, Raj Rudra, Amit Carbonell, J. Siekmann, J. value-based item packages mining ILP patterns integer integer linear programming Traditional methods for discovering frequent patterns from large databases assume equal weights for all items of the database. In the real world, managerial decisions are based on economic values attached to the item sets. In this paper, we first introduce the concept of the value based frequent item packages problems. Then we provide an integer linear programming (ILP) model for value based optimization problems in the context of transaction data. The specific problem discussed in this paper is to find an optimal set of item packages (or item sets making up the whole transaction) that returns maximum profit to the organization under some limited resources. The specification of this problem allows us to solve a number of practical decision problems, by applying the existing and new ILP solution techniques. The model has been implemented and tested with real life retail data. The test results are reported in the paper. 2006 Book Chapter http://hdl.handle.net/20.500.11937/44572 10.1007/11677437_7 Springer-Verlag restricted
spellingShingle value-based item packages
mining
ILP
patterns
integer
integer linear programming
Achuthan, Narasimaha
Gopalan, Raj
Rudra, Amit
Mining value-based item packages - An integer programming approach
title Mining value-based item packages - An integer programming approach
title_full Mining value-based item packages - An integer programming approach
title_fullStr Mining value-based item packages - An integer programming approach
title_full_unstemmed Mining value-based item packages - An integer programming approach
title_short Mining value-based item packages - An integer programming approach
title_sort mining value-based item packages - an integer programming approach
topic value-based item packages
mining
ILP
patterns
integer
integer linear programming
url http://hdl.handle.net/20.500.11937/44572