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首页> 外文期刊>International Journal of Web Engineering and Technology >Identifying web navigation behaviour and patterns automatically from clickstream data
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Identifying web navigation behaviour and patterns automatically from clickstream data

机译:从点击流数据中自动识别Web导航行为和模式

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摘要

A user's clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user's navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.
机译:用户的点击流(例如在服务器端日志中找到的点击流)可以是与用户导航网站的方式有关的丰富数据源,但是在这些日志中找到的详细信息的数量和级别使您难以识别并对特定的导航模式进行分类。在本文中,我们描述了三步自动模式发现(APD)方法,该工具利用顺序挖掘基于两个基本导航元素级别来提取用户的导航路线。本文描述了使用APD的两项研究。首先是利用APD分析教育网站的使用情况;第二部分介绍了APD如何用于改进大学部门技术支持网站的设计。

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