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Mining Web navigation patterns with a path traversal graph

机译:使用路径遍历图挖掘Web导航模式

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摘要

Understanding the navigational behaviour of website visitors is a significant factor of success in the emerging business models of electronic commerce and even mobile commerce. However, Web traversal patterns obtained by traditional Web usage mining approaches are ineffective for the content management of websites. They do not provide the big picture of the intentions of the visitors. The Web navigation patterns, termed throughout-surfing patterns (TSPs) as defined in this paper, are a superset of Web traversal patterns that effectively display the trends toward the next visited Web pages in a browsing session. TSPs are more expressive for understanding the purposes of website visitors. In this paper, we first introduce the concept of throughout-surfing patterns and then present an efficient method for mining the patterns. We propose a compact graph structure, termed a path traversal graph, to record information about the navigation paths of website visitors. The graph contains the frequent surfing paths that are required for mining TSPs. In addition, we devised a graph traverse algorithm based on the proposed graph structure to discover the TSPs. The experimental results show the proposed mining method is highly efficient to discover TSPs.
机译:在新兴的电子商务甚至移动商务中,了解网站访问者的导航行为是成功的重要因素。但是,通过传统的Web使用情况挖掘方法获得的Web遍历模式对网站的内容管理无效。他们没有提供游客意图的全景。 Web导航模式(在本文中定义为整个浏览模式(TSP))是Web遍历模式的超集,可有效显示浏览会话中下一个访问的网页的趋势。 TSP对于理解网站访问者的目的更具表达力。在本文中,我们首先介绍了整体冲浪模式的概念,然后提出了一种有效的模式挖掘方法。我们提出一种紧凑的图结构,称为路径遍历图,以记录有关网站访问者导航路径的信息。该图包含挖掘TSP所需的频繁冲浪路径。此外,我们基于提出的图结构设计了图遍历算法以发现TSP。实验结果表明,提出的挖掘方法是发现TSP的高效方法。

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