Séminaires RALI-OLST

Distributional Semantics for Robust Automatic Summarization

Jackie Cheung (jcheung <at> cs (point) mcgill (point) ca)

Université McGill

Le mercredi 4 novembre 2015 à 11 h 30

Salle 3195, Pavillon André-Aisenstadt


In automatic summarization, interest is shifting ever more from bigram-based extractive techniques towards text-to-text and fully abstractive methods. A major challenge in the field is to determine what kind of semantic representations is rich enough to support useful inferences yet easily learnable from data. In this talk, I discuss how distributional semantics (DS) can help to determine the content and form of summaries in support of these goals. First, I present a method that integrates phrasal DS representations into a probabilistic content model in order to learn about the important events and slots in a domain. This method aims to use automatically learned domain knowledge to inform content selection, and is validated by an extractive summarization experiment. Then, I discuss the use of DS within a text-to-text sentence fusion setting, in which parts of multiple source text sentences are fused together to form a novel output sentence. This work points to the potential of DS to support broad-coverage natural language generation applications.


Suivez ce lien pour vous inscrire à la liste de diffusion RALI-OLST.
http://rali.iro.umontreal.ca/rali/?q=fr/node/1631

Liste de tous les séminaires pour l'année :

1991 1992 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024