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

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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.

This article is categorized under:

  • Application Areas > Science and Technology
  • Algorithmic Development > Association Rules
  • Algorithmic Development > Web Mining
User navigation model for a typical e‐commerce application. It is modeled using a weighted direct graph with nodes representing the typical web items and directed edges representing user navigation from one web item to another; the weights of edges are regularly updated based on statistics in server logs
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Comparison between two approaches in terms of revenue generation: (1) No priority scheduling, no Admission Control; (2) Combination of Admission Control and Priority Scheduling based on both SLA and Association Rules
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Comparison between two approaches in terms of revenue generation: (1) No priority scheduling, no Admission Control; (2) Combination of Admission Control and Priority Scheduling based on SLAs
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Comparison between two approaches in terms of revenue generation: (1) Neither priority scheduling nor Admission Control is applied; (2) Combination of Admission Control and Priority Scheduling based on Association Rules is applied
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Comparison between two approaches in terms of revenue generation: (1) No priority scheduling, no Admission Control; (2) Priority Scheduling based on SLA, No Admission Control
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Algorithmic Development > Association Rules
Algorithmic Development > Web Mining
Application Areas > Science and Technology

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