Visual Data Mining of Web Navigational Data

Jiyang Chen, Tong Zheng, William Thorne, Osmar R Zaiane, R. Goebel
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引用次数: 17

Abstract

Discovering web navigational trends and understanding data mining results is undeniably advantageous to web designers and web-based application builders. It is also desirable to interactively investigate web access data and patterns, to allows ad-hoc discovery and examination of patterns that are not apriori known. Visualizing the usage data in the context of the web site structure is of major importance, as it puts web access requests and their connectivity in perspective. Various visualization tools have been developed for this task, but often fail to provide visual data mining functionalities to generate new patterns. Here we present our visual data mining system, WebViz, which allows interactive investigation of web usage data within their structure context, as well as ad-hoc knowledge pattern discovery on web navigational behaviour.
Web导航数据的可视化数据挖掘
不可否认,发现网络导航趋势和理解数据挖掘结果对网页设计师和基于web的应用程序构建者是有利的。交互式地调查web访问数据和模式也是可取的,以允许对非先天已知的模式进行特别的发现和检查。在网站结构的上下文中可视化使用数据是非常重要的,因为它可以透视web访问请求及其连接性。已经为这项任务开发了各种可视化工具,但通常不能提供生成新模式的可视化数据挖掘功能。在这里,我们展示了我们的可视化数据挖掘系统WebViz,它允许在其结构上下文中对web使用数据进行交互式调查,以及对web导航行为进行特别的知识模式发现。
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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