Key points are not available for this paper at this time.
Describes an approach automatically to classify and evaluate publicly accessible World Wide Web sites. The suggested methodology is equally valuable for analyzing content and hypertext structures of commercial, educational and nonprofit organizations. Outlines a research methodology for model building and validation and defines the most relevant attributes of such a process. A set of operational criteria for classifying Web sites is developed. The introduced software tool supports the automated gathering of these parameters, and thereby assures the necessary ``critical mass'' of empirical data. Based on the preprocessed information, a multi-methodological approach is chosen that comprises statistical clustering, textual analysis, supervised and nonsupervised neural networks and manual classification for validation purposes.
Bauer et al. (Wed,) studied this question.