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

Xue, J. and Jarvis, S. (2017) Mining association rules for admission control and service differentiation in e-commerce applications. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 8(3), pp. 1-9. 1942-4795.

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Xue_James_Jarvis_Stephen_WOL_2018_Mining_association_rules_for_admission_control_and_service_differentiation_in_e_commerce_applications.pdf - Published Version
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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 maximise 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 into consideration: a) only final purchase requests result in company revenue; b) any other request can potentially lead to a 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 maximisation.

Uncontrolled Keywords:

admission control, association rule, cloud computing, e-commerce, service differentiation

Creators:

Xue, J. and Jarvis, S.

Faculties, Divisions and Institutes:

Faculties > Faculty of Arts, Science & Technology > Computing

Date:

27 November 2017

Date Type:

Acceptance

Page Range:

pp. 1-9

Journal or Publication Title:

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

Volume:

Number:

Number of Pages:

Language:

English

DOI:

10.1002/widm.1241

ISSN:

1942-4795

Status:

Published / Disseminated

Refereed:

Yes

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