Machine learning-based url categorization system with selection between more and less specific category labels

Abstract

Disclosed is technology for choosing between alternative category labels tentatively assigned to tens of thousands of webpages by a classifier ensemble running on processors, applying the classifier ensemble with a sensitive category classifier, a non-sensitive category classifier, a title and metadata classifier and a heuristic classifier to tens of thousands of webpages. Also disclosed is applying a post processor to outputs of the classifier ensemble and tentatively assigning at least two category labels for non-sensitive categories for webpages; two category labels, automatically determining that at least one but not all of the tentatively assigned category labels is a general label and de-assigning the general label; saving the category label that is not de-selected to the webpage; and distributing the assigned category labels for at least some of the tens of thousands of webpages for use in controlling access to webpages by users on user systems protected using the assigned labels.