Entity detection and tracking is a relatively new addition to the repertoire of natural language tasks. In this paper, we present a statistical language-independent framework for ...
Radu Florian, Hany Hassan, Abraham Ittycheriah, Ho...
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
We present a simple method for language independent and task independent text categorization learning, based on character-level n-gram language models. Our approach uses simple in...
This paper describes our approaches to the opinion retrieval and blog distillation tasks for the Blog Track. For opinion retrieval we employ a two-stage framework consisting of ke...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...