We present the first report of automatic sentiment summarization in the legal domain. This work is based on processing a set of legal questions with a system consisting of a semi...
Jack G. Conrad, Jochen L. Leidner, Frank Schilder,...
Scoring sentences in documents given abstract summaries created by humans is important in extractive multi-document summarization. In this paper, we formulate extractive summariza...
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 ...
This paper investigates the impact of automatic sentence segmentation on speech summarization using the ICSI meeting corpus. We use a hidden Markov model (HMM) for sentence segmen...
mation science has shown that human abstractors extract sentences for summaries based on the hierarchical structure of documents; however, the existing automatic summarization mode...