Web site classification based on key resources

Automatic Web site classification has a wide application prospect. However, there is a little research on the Web site classification. Many methods represent the Web site as normal text and still use the methods of text classification. But Web sites are combination of many Web pages via hyperlinks, so the methods of text classification are not suitable for Web sites. This paper proposes a new approach to Web site classification. First of all, we get the key resources of Web site through a reasonable pruning strategy. Then abstract the topic vector of Web site from the key resources, according to the Web site´s structure information and content information. To reflect the structure information of the Web site, we use an improved vector space model which includes both structure feature words and content feature words to represent the topic vector of the Web site.