Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Mining association rules for admission control and service differentiation in e-commerce applications

Tools
- Tools
+ Tools

Xue, James and Jarvis, Stephen A. (2018) Mining association rules for admission control and service differentiation in e-commerce applications. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8 (3). e1241. doi:10.1002/widm.1241

[img]
Preview
PDF
WRAP-mining-association-rules-admission-control-service-differentiation-e-commerce-applications-Jarvis-2018.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons: Attribution-Noncommercial 4.0.

Download (1528Kb) | Preview
Official URL: http://dx.doi.org/10.1002/widm.1241

Request Changes to record.

Abstract

Workload demands in e-commerce applications are very dynamic in nature, therefore it is essential for internet service providers to manage server resources effectively to maximize total revenue in server overloading situations. In this paper, a data mining technique is applied to a typical e-commerce application model for identification of composite association rules that capture user navigation patterns. Two algorithms are then developed based on the derived rules for admission control, service differentiation, and priority scheduling. Our approach takes the following aspects into consideration: (a) only final purchase requests result in company revenue; (b) any other request can potentially lead to final purchase, depending upon the likelihood of the navigation sequence that starts from current request and leads to final purchase; (c) service differentiation and priority assignment are based on aggregated confidence and average support of the composite association rules. As identification of composite association rules and computation of confidence and support of the rules can be pre-computed offline, the proposed approach incurs minimum performance overheads. The evaluation results suggest that the proposed approach is effective in terms of request management for revenue maximization.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Data mining, Web usage mining, Electronic commerce -- Computer network resources, Association rule mining, Cloud computing, Electronic digital computers -- Workload
Journal or Publication Title: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Publisher: John Wiley & Sons Ltd.
ISSN: 1942-4787
Official Date: May 2018
Dates:
DateEvent
May 2018Published
5 March 2018Available
27 November 2017Accepted
Volume: 8
Number: 3
Article Number: e1241
DOI: 10.1002/widm.1241
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us