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: Ahmed Giha, Fatma Elsheikh
Format: Thesis
Published: 2004
Subjects:
Online Access:http://shdl.mmu.edu.my/787/
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author Ahmed Giha, Fatma Elsheikh
author_facet Ahmed Giha, Fatma Elsheikh
author_sort Ahmed Giha, Fatma Elsheikh
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 2025-11-14T17:59:19Z
format Thesis
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institution Multimedia University
institution_category Local University
last_indexed 2025-11-14T17:59:19Z
publishDate 2004
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spelling mmu-7872010-07-02T04:23:42Z http://shdl.mmu.edu.my/787/ Data Mining Techniques For E-Commerce Applications Ahmed Giha, Fatma Elsheikh HF5548.7-5548.85 Industrial psychology 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. 2004-04 Thesis NonPeerReviewed Ahmed Giha, Fatma Elsheikh (2004) Data Mining Techniques For E-Commerce Applications. Masters thesis, Multimedia University. http://myto.perpun.net.my/metoalogin/logina.php
spellingShingle HF5548.7-5548.85 Industrial psychology
Ahmed Giha, Fatma Elsheikh
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 HF5548.7-5548.85 Industrial psychology
url http://shdl.mmu.edu.my/787/
http://shdl.mmu.edu.my/787/