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: Ahmed Giha, Fatma Elsheikh
Format: Thesis
Published: 2004
Subjects:
HF5548.7-5548.85 Industrial psychology
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-mmu-ep.787
record_format uketd_dc
spelling my-mmu-ep.7872010-07-02T04:23:42Z Data Mining Techniques For E-Commerce Applications 2004-04 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 http://shdl.mmu.edu.my/787/ http://myto.perpun.net.my/metoalogin/logina.php masters Multimedia University Research Library
institution Multimedia University
collection MMU Institutional Repository
topic HF5548.7-5548.85 Industrial psychology
spellingShingle HF5548.7-5548.85 Industrial psychology
Ahmed Giha, Fatma Elsheikh
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 Ahmed Giha, Fatma Elsheikh
author_facet Ahmed Giha, Fatma Elsheikh
author_sort Ahmed Giha, Fatma Elsheikh
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_ 1747829216275070976

Similar Items