Website classification

A computer system for classifying a test website, the computer system comprising:

• a processor configured to:
• for each multiple neighbour websites, calculate an importance value between the test website and one of the multiple neighbour websites, each of the multiple neighbour websites being connected to the test website by way of one or more hyperlinks;
• build a graph of nodes and directed edges, a node representing a website and a directed edge representing a hyperlink between websites;
• for each node in the graph, calculate a classification value and classifying the node based on the classification value, wherein at least one node is a website on a whitelist, corresponding to a predetermined classification value;
• select one or more of the multiple neighbour websites on the graph, based on the importance value corresponding to the one or more of the multiple neighbour websites;
• for each website in the selected one or more of the multiple neighbour websites and the test website:
• determine content features for the website, and
• evaluating a trained machine learning model for the website, based on the content features to calculate multiple output values for the website, wherein the trained machine learning model is trained by calculating a classification value for each node on the graph and minimising a cost between the classification value and node labels obtained from a whitelist and/or blacklist and aggregating corresponding output values from a pre-trained machine learning model for each of the test website and the selected one or more of the multiple neighbour websites to calculate the classification value for each node on the graph;
• and
• aggregate corresponding output values for each of the test website and the selected one or more of the multiple neighbour websites to calculate a classification value that classifies the test website.