This paper reports the first part of a project that aims to develop a knowledge extraction and knowledge discovery system that extracts causal knowledge from textual databases. In...
Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative ap...
We present a corpus-based method for estimating the importance of sentences. Our main contribution is two-fold. First, we introduce the idea of using the increasing amount of manu...
This paper presents a supervised machine learning approach for summarizing legal documents. A commercial system for the analysis and summarization of legal documents provided us wi...
This paper presents a new model for word alignments between parallel sentences, which allows one to accurately estimate different parameters, in a computationally efficient way. A...