Abstract

ROJAS SIMON, Jonathan; LEDENEVA, Yulia  and  GARCIA-HERNANDEZ, René Arnulfo. Calculating the Upper Bounds for Multi-Document Summarization using Genetic Algorithms. Comp. y Sist. [online]. 2018, vol.22, n.1, pp.11-26. ISSN 2007-9737.  https://doi.org/10.13053/cys-22-1-2903.

Over the last years, several Multi-Document Summarization (MDS) methods have been presented in Document Understanding Conference (DUC), workshops. Since DUC01, several methods have been presented in approximately 268 publications of the state-of-the-art, that have allowed the continuous improvement of MDS, however in most works the upper bounds were unknowns. Recently, some works have been focused to calculate the best sentence combinations of a set of documents and in previous works we have been calculated the significance for single-document summarization task in DUC01 and DUC02 datasets. However, for MDS task has not performed an analysis of significance to rank the best multi-document summarization methods. In this paper, we describe a Genetic Algorithm-based method for calculating the best sentence combinations of DUC01 and DUC02 datasets in MDS through a Meta-document representation. Moreover, we have calculated three heuristics mentioned in several works of state-of-the-art to rank the most recent MDS methods, through the calculus of upper bounds and lower bounds.

Keywords : Topline; multi-document summarization; genetic algorithms; upper bounds; significance.

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