Adaptive Filtering of Newswire Stories using Two-Level Clustering

Adaptive filtering of news is an area of information retrieval gaining substantial interest as services become more available on the Internet. This paper reports on a number of experiments involving a two-level clustering approach using a variety of techniques including threshold adaptation, topic vocabulary adaptation and both noun phrase and named entity adaptation. Our goal in this exploratory research is to empirically compare alternative configurations of our filtering approach that will allow us to better understand the relative value of the component subsystems.