A Cluster-Based Approach to Broadcast News

Abstract

We present an approach to detection and tracking of topics in multilingual broadcast news based upon a dynamic clustering scheme. Our approach derives from a system used to filter Web searches from multiple sources, with extensions for pipelining document clusters, part-of-speech tagging and extraction of named entities for use in an extended similarity measure.