The use of web structure and content to identify subjectively interesting web usage patterns

Author:

Cooley Robert1

Affiliation:

1. KXEN, Inc., San Francisco, CA

Abstract

The discipline of Web Usage Mining has grown rapidly in the past few years, despite the crash of the e-commerce boom of the late 1990s. Web Usage Mining is the application of data mining techniques to Web clickstream data in order to extract usage patterns. Yet, with all of the resources put into the problem, claims of success have been limited and are often tied to specific Web site properties that are not found in general. One reason for the limited success has been a component of Web Usage Mining that is often overlooked---the need to understand the content and structure of a Web site. The processing and quantification of a Web sites content and structure for all but completely static and single frame Web sites is arguably one of the most difficult tasks to automate in the Web Usage Mining process. This article shows that, not only is the Web Usage Mining process enhanced by content and structure, it cannot be completed without it. The results of experiments run on data from a large e-commerce site are presented to show that proper preprocessing cannot be completed without the use of Web site content and structure, and that the effectiveness of pattern analysis is greatly enhanced.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference28 articles.

1. Balabanovic M. and Shoham Y. 1995. Learning information retrieval agents: Experiments with automated web browsing. In On-line Working Notes of the AAAI Spring Symposium Series on Information Gathering from Distributed Heterogeneous Environments.]] Balabanovic M. and Shoham Y. 1995. Learning information retrieval agents: Experiments with automated web browsing. In On-line Working Notes of the AAAI Spring Symposium Series on Information Gathering from Distributed Heterogeneous Environments.]]

2. Bonissone P. P. and Decker K. S. 1986. Selecting uncertainty calculi and granularity: An experiment in trading-off precision and complexity. Uncert. Artif. Intell. 2217--2247.]] Bonissone P. P. and Decker K. S. 1986. Selecting uncertainty calculi and granularity: An experiment in trading-off precision and complexity. Uncert. Artif. Intell. 2217--2247.]]

Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3