Apparatus and methods for classification of web sites

Abstract

Apparatus and methods for classifying web sites are provided. With the apparatus and methods, traffic data is obtained for a plurality of web sites. This patterns, or templates, for each web site are generated based on this traffic data and the patterns are clustered into classes of web sites using a clustering algorithm. The clusters, or classes, are then profiled to generate a template for each class. The template for each class is generated by first shifting the patterns for each web site that is part of the class to compensate for effects like time zone differences, if any, and then identifying a pattern that is most similar to all of the patterns in the class. Once the template for each class is generated, this template is then used with traffic data from a new web site to classify the new web site into one of the existing classes. In other words, when traffic data for a new web site is received, a pattern for the traffic data of the new web site is generated and compared to the templates for the various classes. If a matching class template is identified, the new web site is classified into the corresponding class. If the pattern for the new web site does not match any of the existing templates, a new template and class may be generated based on the pattern for the new web site.