—We introduce a novel set of social network analysis based algorithms for mining the Web, blogs, and online forums to identify trends and find the people launching these new tren...
Peter A. Gloor, Jonas Krauss, Stefan Nann, Kai Fis...
Online service providers are engaged in constant conflict with miscreants who try to siphon a portion of legitimate traffic to make illicit profits. We study the abuse of “tr...
Tyler Moore, Nektarios Leontiadis, Nicolas Christi...
In this paper we address the problem of unsupervised Web data extraction. We show that unsupervised Web data extraction becomes feasible when supposing pages that are made up of r...
Existing categorization algorithms deal with homogeneous Web objects, and consider interrelated objects as additional features when taking the interrelationships with other types o...
The problem of measuring similarity between web pages arises in many important Web applications, such as search engines and Web directories. In this paper, we propose a novel neig...