Taking into account Inter-sentence Similarity for Update Summarization
Abstract
Following Gillick and Favre (2009), a lot
of work about extractive summarization
has modeled this task by associating two
contrary constraints: one aims at maximizing
the coverage of the summary with
respect to its information content while
the other represents its size limit. In this
context, the notion of redundancy is only
implicitly taken into account. In this article,
we extend the framework defined
by Gillick and Favre (2009) by examining
how and to what extent integrating semantic
sentence similarity into an update
summarization system can improve its results.
We show more precisely the impact
of this strategy through evaluations performed
on DUC 2007 and TAC 2008 and
2009 datasets.
Origin : Files produced by the author(s)