Distinguishing Specific and Daily Topics

Abstract

The task of distinguishing specific and daily topics is useful in many applications such as event chronicle and timeline generation, and cross-document event coreference resolution. In this paper, we investigate several numeric features that describe useful statistical information for this task, and propose a novel Bayesian model for distinguishing specific and daily topics from a collection of documents based on documents' content. The proposed Bayesian model exploits mixture of Poisson distributions for modeling probability distributions of the numeric features. The experimental results show that our approach is promising to solve this problem.