SummTriver is a tool for evaluating summaries automatically without using reference summaries, unlike ROUGE. SummTriver, utilizes multiple trivergences to achieve this and has shown promising results, especially in data from summarization campaigns. SummTriver has been tested, among others, with The PUCES corpus.

SummTriver system is well suitable for compare and evaluate automatic text summarization systems (with ou without references) like SummTriver, FRESA, SIMetrix or ROUGE.

• Download SummTriver | Dependences SummTriver sur Docker

• SummTriver information sur GitHub

  • Comment télécharge SummTriver?
  • Comment exécuter SummTriver?
  • Comment intérpréter les résultsts?

• How to cite SummTriver?

  L. A. Cabrera-Diego and J-M. Torres-Moreno, SummTriver: A new trivergent model to evaluate summaries automatically without human references, Data & Knowledge Engineering, vol. 113, pp. 184–197, 2018

  
  	@article{DKE:2018:SummTriver,
  	author = "Luis Adrián Cabrera-Diego and Juan-Manuel Torres-Moreno",
  	title = "SummTriver: A new trivergent model to evaluate summaries automatically without human references",
  	journal = "Data & Knowledge Engineering",
  	volume = "113",
  	pages = "184 - 197",
  	year = "2018",
  	issn = "0169-023X",
  	doi = "doi.org/10.1016/j.datak.2017.09.001"
         }
  
  

Contact : Juan-Manuel Torres & Luis Adrian Cabrera Diego
http://lia.univ-avignon.fr / Universite d'Avignon, France
juan *-* manuel *dot* torres *at* univ-avignon *dot* fr | adrian *dot* 9819 *at* gmail *dot* com