Data Mining Techniques for E-Commerce Applications

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...

Full description

Saved in:
Bibliographic Details
Main Author: Fatma Elsheikh Ahmed Giha
Format: Thesis
Published: 2004
Subjects:
HF5546-5548.6 Office management
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-mmu-ep.144
record_format uketd_dc
spelling my-mmu-ep.1442010-02-23T08:38:07Z Data Mining Techniques for E-Commerce Applications 2004 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 http://shdl.mmu.edu.my/144/ http://vlib.mmu.edu.my/diglib/login/dlusr/login.php masters Multimedia University Research Library
institution Multimedia University
collection MMU Institutional Repository
topic HF5546-5548.6 Office management
spellingShingle HF5546-5548.6 Office management
Fatma Elsheikh Ahmed Giha,
Data Mining Techniques for E-Commerce Applications
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.
format Thesis
qualification_level Master's degree
author Fatma Elsheikh Ahmed Giha,
author_facet Fatma Elsheikh Ahmed Giha,
author_sort Fatma Elsheikh Ahmed Giha,
title Data Mining Techniques for E-Commerce Applications
title_short 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_sort data mining techniques for e-commerce applications
granting_institution Multimedia University
granting_department Research Library
publishDate 2004
_version_ 1747829092430905344

Similar Items