Visually mining Web user clickpaths

T. Mah, Y. Li
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引用次数: 1

Abstract

As powerful as clickpath mining methods can be, they often lead to huge incomprehensible and non-interesting result sets. Our clickpath mining practice at MSN was faced with challenges of keeping analysts closer to the data exploration process, revealing powerful insight from clickpath mining that business owners can directly act upon. These challenges stressed the importance of an interactive and visual representation of clickpath mining results. Most products today that can perform clickpath visualization do so by presenting massive cross-weaving web graphs. We present a new type of clickpath visualization which focuses only on clickpaths of interest, simplifying the visualization space while still retaining the same degree of mineable knowledge in the data. We also describe visualization techniques we have used to enhance the detection of interesting clickpath patterns from data, and provide a real-life case study that has benefited from the use of our implemented clickpath visualizer PAVE.
可视化地挖掘Web用户点击路径
尽管点击路径挖掘方法很强大,但它们通常会导致大量难以理解和无趣的结果集。我们在MSN的点击路径挖掘实践面临着让分析师更接近数据探索过程的挑战,从点击路径挖掘中揭示出商业所有者可以直接采取行动的强大洞察力。这些挑战强调了点击路径挖掘结果的交互式和可视化表示的重要性。今天,大多数可以执行点击路径可视化的产品都是通过呈现大量交叉编织的网络图形来实现的。我们提出了一种新型的点击路径可视化,它只关注感兴趣的点击路径,简化了可视化空间,同时仍然保留了数据中相同程度的可挖掘知识。我们还描述了我们用来增强从数据中检测有趣的点击路径模式的可视化技术,并提供了一个从使用我们实现的点击路径可视化工具PAVE中受益的现实案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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