Two-Stage Method for Grouping News with Similar Topics

Abstract

This paper is devoted to event detection as part of news stream analysis. An event is regarded as a group of news texts dedicated to one real-world fact or situation. We analyze news from Russian news agencies. A two-stage clustering method is proposed, which combines a rough clustering algorithm used at the first stage and a refinement classifier used at the second stage. In addition, we present an open labeled dataset for news event detection, which is based on the Yandex News service. Empirical evaluation of the proposed method on this dataset proves its effectiveness for event detection in news texts.