Mining the information architecture of the WWW using automated website boundary detection.

The world wide web has two main forms of architecture, the first is that which is explicitly encoded into web pages, and the second is that which is implied by the web content, particularly pertaining to look and feel. The latter is exemplified by the concept of a website, a concept that is only loosely defined, although users intuitively understand it. The Website Boundary Detection (WBD) problem is concerned with the task of identifying the complete collection of web pages/resources that are contained within a single website. Whatever the case, the concept of a website is used with respect to a number of application domains including; website archiving, spam detection, and www analysis. In the context of such applications it is beneficial if a website can be automatically identified. This is usually done by identifying a website of interest in terms of its boundary, the so called WBD problem. In this paper seven WBD techniques are proposed and compared, four statistical techniques where the web data to be used is obtained apriori, and three dynamic techniques where the data to be used is obtained as the process progresses. All seven techniques are presented in detail and evaluated.