WWW2009 EPrints

Link Based Small Sample Learning for Web Spam Detection

This item is a Poster.

Published Version

PDF (515Kb)


Robust statistical learning based web spam detection sys- tem often requires large amounts of labeled training data. However, labeled samples are more difficult, expensive and time consuming to obtain than unlabeled ones. This pa- per proposed link based semi-supervised learning algorithms to boost the performance of a classifier, which integrates the traditional Self-training with the topological dependency based link learning. The experiments with a few labeled samples on standard WEBSPAM-UK2006 benchmark showed that the algorithms are effective.

Export Record As...

About this site

This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.


We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it... [this has now happened, this site is now static]