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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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 |