Mining client-side activity for personalization

Kurt D. Fenstermacher, Mark Ginsburg
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引用次数: 34

Abstract

"Garbage in. garbage out" is a well-known phrase in computer analysis, and one that comes to mind when mining Web data to draw conclusions about Web users. The challenge is that data analysts wish to infer patterns of client-side behavior from server-side data. However, because only a fraction of the user's actions ever reach the Web server, analysts must rely on incomplete data. In this paper, we propose a client-side monitoring system that is unobtrusive and supports flexible data collection. Moreover, the proposed framework encompasses client-side applications beyond the Web browser. Expanding monitoring beyond the browser to incorporate standard office productivity tools enables analysts to derive a much richer and more accurate picture of user behavior on the Web.
挖掘客户端活动以实现个性化
“垃圾。“垃圾输出”是计算机分析中一个众所周知的短语,在挖掘Web数据以得出关于Web用户的结论时,人们会想到这个短语。挑战在于数据分析人员希望从服务器端数据推断客户端行为模式。然而,由于只有一小部分用户的操作到达了Web服务器,因此分析人员必须依赖不完整的数据。在本文中,我们提出了一个客户端监控系统,它不引人注目,并支持灵活的数据收集。此外,建议的框架还包括Web浏览器之外的客户端应用程序。将监视扩展到浏览器之外,将标准的办公生产力工具合并在一起,使分析人员能够获得更丰富、更准确的Web用户行为图像。
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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