Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn
published: Jan. 28, 2008, recorded: September 2007, views: 3057
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
We compare a wide range of semi-supervised learning techniques both for Web spam filtering and for telephone user churn classification. Semisupervised learning has the assumption that the label of a node in a graph is similar to those of its neighbors. In this paper we measure this phenomenon both for Web spam and telco churn. We conclude that spam is often linked to spam while honest pages are linked to honest ones; similarly churn occurs in bursts in groups of a social network.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !