Data Mining Techniques for E-Commerce Applications

Data mining is a process of nontrivial extraction of implicit, previously unknown, and potentially useful information from large databases. This thesis provides an overview of data mining techniques and their modifications along with applications to e-Commerce. E-commerce problems are in general con...

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Main Author: Fatma Elsheikh Ahmed Giha
Format: Thesis
Published: 2004
Subjects:
Online Access:http://shdl.mmu.edu.my/144/
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author Fatma Elsheikh Ahmed Giha,
author_facet Fatma Elsheikh Ahmed Giha,
author_sort Fatma Elsheikh Ahmed Giha,
building MMU Institutional Repository
collection Online Access
description Data mining is a process of nontrivial extraction of implicit, previously unknown, and potentially useful information from large databases. This thesis provides an overview of data mining techniques and their modifications along with applications to e-Commerce. E-commerce problems are in general considered aa cross-selling, customer profiling and segmentation , fraud detection, and many others. Simple association rules, generalized association rules, profile association rules, and generalized profile association rules are presented to build customer profiles, based on association rules mining technique. Interestingness measures are considered to find the most interesting association rules for customer profiling and segmentation.
first_indexed 2025-11-14T17:56:35Z
format Thesis
id mmu-144
institution Multimedia University
institution_category Local University
last_indexed 2025-11-14T17:56:35Z
publishDate 2004
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repository_type Digital Repository
spelling mmu-1442010-02-23T08:38:07Z http://shdl.mmu.edu.my/144/ Data Mining Techniques for E-Commerce Applications Fatma Elsheikh Ahmed Giha, HF5546-5548.6 Office management Data mining is a process of nontrivial extraction of implicit, previously unknown, and potentially useful information from large databases. This thesis provides an overview of data mining techniques and their modifications along with applications to e-Commerce. E-commerce problems are in general considered aa cross-selling, customer profiling and segmentation , fraud detection, and many others. Simple association rules, generalized association rules, profile association rules, and generalized profile association rules are presented to build customer profiles, based on association rules mining technique. Interestingness measures are considered to find the most interesting association rules for customer profiling and segmentation. 2004 Thesis NonPeerReviewed Fatma Elsheikh Ahmed Giha, (2004) Data Mining Techniques for E-Commerce Applications. Masters thesis, Multimedia University. http://vlib.mmu.edu.my/diglib/login/dlusr/login.php
spellingShingle HF5546-5548.6 Office management
Fatma Elsheikh Ahmed Giha,
Data Mining Techniques for E-Commerce Applications
title Data Mining Techniques for E-Commerce Applications
title_full Data Mining Techniques for E-Commerce Applications
title_fullStr Data Mining Techniques for E-Commerce Applications
title_full_unstemmed Data Mining Techniques for E-Commerce Applications
title_short Data Mining Techniques for E-Commerce Applications
title_sort data mining techniques for e-commerce applications
topic HF5546-5548.6 Office management
url http://shdl.mmu.edu.my/144/
http://shdl.mmu.edu.my/144/