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首页> 外文会议>International Workshop on DataBase Management and Application over Networks(DBMAN 2007); International Workshop on Emerging Trends of Web Technologies and Applications(WebETrends 2007; International Workshop on Process Aware Information Systems(PAIS 2007 >Mining Web Transaction Patterns in an Electronic Commerce Environment
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Mining Web Transaction Patterns in an Electronic Commerce Environment

机译：在电子商务环境中挖掘Web交易模式

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摘要

Association rule mining discovers most of the users' purchasing behaviors from transaction database. Association rules are valuable for cross-marking and attached mailing applications. Other applications include catalog design, add-on sales, store layout, and customer segmentation based on buying patterns. Web traversal pattern mining discovers most of the users' access patterns from web logs. This information can provide navigation suggestions for web users such that appropriate actions can be adopted. Web transaction pattern mining discovers not only the pure navigation behaviors but also the purchasing behaviors of customers. In this paper, we propose an algorithm TWA (Integrating Web traversal patterns and Association rules) for mining web transaction patterns in the electronic commerce environment. Our IWA algorithm takes both the traveling and purchasing behaviors of customers into consideration at the same time. The experimental results show that IWA algorithm can simultaneously and efficiently discover traveling and purchasing behaviors for most of customers.
机译：关联规则挖掘从交易数据库中发现大多数用户的购买行为。关联规则对于交叉标记和附加的邮件应用程序很有价值。其他应用程序包括目录设计，附加销售，商店布局以及基于购买模式的客户细分。 Web遍历模式挖掘可从Web日志中发现大多数用户的访问模式。此信息可以为Web用户提供导航建议，以便可以采取适当的操作。 Web事务模式挖掘不仅发现纯导航行为，而且发现客户的购买行为。在本文中，我们提出了一种用于在电子商务环境中挖掘Web交易模式的TWA（集成Web遍历模式和关联规则）算法。我们的IWA算法同时考虑了客户的旅行和购买行为。实验结果表明，IWA算法可以同时并有效地发现大多数客户的旅行和购买行为。

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