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 develops a new paradigm for relational learning which allows for the representation and learning of relational information using propositional means. This paradigm sugg...
Wrapper is a traditional method to extract useful information from Web pages. Most previous works rely on the similarity between HTML tag trees and induced template-dependent wrap...
In this paper, we propose a novel framework for extractive summarization. Our framework allows the summarizer to adapt and improve itself. Experimental results show that our summa...
Domain shift is a challenging issue in dialogue management. This paper shows how to extract domain knowledge for dialogue model adaptation. The basic semantic concepts are derived ...