Progressive filtering on the web: The press reviews case study

Abstract

Progressive Filtering is a hierarchical classification technique framed within the local classifier per node approach where each classifier is entrusted with deciding whether the input in hand can be forwarded or not to its children. In this chapter, we illustrate the effectiveness of Progressive Filtering on the Web, focusing on the task of automatically creating press reviews. To this end, we present NEWS.MAS, a multiagent system aimed at: (i) extracting information from online newspapers by using suitable wrapper agents, each associated with a specific information source, (ii) categorizing news articles according to a given taxonomy, and (iii) providing user feedback to improve the performance of the system depending on user needs and preferences. © 2011 Springer-Verlag Berlin Heidelberg.