根据代表性页面的识别,制定如何改进网站内容的指导方针

Sebastián A. Ríos, J. D. Velásquez, Eduardo S. Vera, H. Yasuda, T. Aoki
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引用次数: 8

摘要

互联网已经成为一个巨大的战场,各组织都在努力保持现有的客户,并获得新的客户。组织拥有的两个重要武器是设计一个好的网站,并为访问者提供有趣的内容。为了改进网站内容,开发了许多工具。然而,很难弄清楚如何应用这些变化。此外,在复杂的Web站点中,这是一项非常重要的任务。我们提出了一种新的方法,该方法使用SOFM和执行反向聚类分析来帮助改进Web站点内容,该分析允许我们从Web站点收集最具代表性的Web页面,并使用这一小组页面作为如何执行这些增强的指导方针。在一个真实的网站上测试了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishing guidelines on how to improve the Web site content based on the identification of representative pages
The Internet has become a big battlefield where organizations are trying to keep their present clients and to gain new ones. Two important weapons that the organizations have are to make a good Web site design and to have a content interesting for the visitors. To improve the Web site content, many tools have been developed. However, it is hard to figure out how to apply these changes. Furthermore, in complex Web sites, this is a non trivial task. We propose a novel approach that helps to improve a Web site content using a SOFM and performing a reverse clustering analysis that allows us to gather the most representative Web pages from a Web site, using this small set of pages as a guideline of how these enhancements should be performed. The effectiveness of the method was tested in a real Web site.
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