Formulation of document summarization as a 0-1 nonlinear programming problem
We proposed a novel text summarization model based on 0-1 non-linear programming problem. This proposed model covers the main content of the given document(s) through sentence assignment. We implemented our model on multi-document summarization task. When comparing our method to several existing summarization methods on an open DUC2001 and DUC2002 datasets, we found that the proposed method could improve the summarization results significantly. The methods were evaluated using ROUGE-1, ROUGE-2 and ROUGE-W metrics. (C) 2012 Elsevier Ltd. All rights reserved.
generic summarization optimization model balancing coverage and diversity weighted combination of arithmetic and geometric means discrete particle swarm optimization estimation of distribution