We define the problem of decomposing human-written summary sentences and propose a novel Hidden Markov Model solution to the problem. Human summarizers often rely on cutting and ...
Abstract--Statistical approaches to document content modeling typically focus either on broad topics or on discourselevel subtopics of a text. We present an analysis of the perform...
Leonhard Hennig, Thomas Strecker, Sascha Narr, Ern...
Documents often contain inherently many concepts reflecting specific and generic aspects. To automatically generate a short summary text of documents on similar topics, it is im...
We present a novel model to represent and assess the discourse coherence of text. Our model assumes that coherent text implicitly favors certain types of discourse relation transi...
We propose a new method for using anaphoric information in Latent Semantic Analysis (lsa), and discuss its application to develop an lsa-based summarizer which achieves a signifi...
Josef Steinberger, Massimo Poesio, Mijail Alexandr...