This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long ...
In this paper we describe work relating to classification of web documents using a graph-based model instead of the traditional vector-based model for document representation. We ...
Adam Schenker, Mark Last, Horst Bunke, Abraham Kan...
Graph-based semi-supervised learning (SSL) algorithms have been successfully used to extract class-instance pairs from large unstructured and structured text collections. However,...
This paper identifies and explores the problem of seed selection in a web-scale crawler. We argue that seed selection is not a trivial but very important problem. Selecting proper...
Fact collections are mostly built using semi-supervised relation extraction techniques and wisdom of the crowds methods, rendering them inherently noisy. In this paper, we propose...