Summarization System . . .
BibTeX
@MISC{Giannakopoulos_summarizationsystem,
author = {George Giannakopoulos and VANGELIS KARKALETSIS and George Vouros and et al.},
title = {Summarization System . . . },
year = {}
}
OpenURL
Abstract
This paper presents a novel automatic method (AutoSummENG) for the evaluation of summarization systems, based on comparing the character n-gram graphs representation of the extracted summaries and a number of model summaries. The presented approach is language neutral, due to its statistical nature, and appears to hold a level of evaluation performance that matches and even exceeds other contemporary evaluation methods. Within this study, we measure the effectiveness of different representation methods, namely word and character n-gram graph and histogram, different n-gram neighbourhood indication methods, as well as different comparison methods between the supplied representations. A theory for the a priori determination of the methods ’ parameters, along with supporting experiments, concludes the study, to provide a complete alternative of existing methods concerning the automatic summary system evaluation process.







