SIGIR'98 posters: The Use of MMR, Diversity-Based Reranking for
Reordering Documents and Producing Summaries
The Use of MMR, Diversity-Based Reranking for Reordering Documents
and Producing Summaries
Jaime Carbonell
Language Technologies Institute,
Carnegie Mellon University,
5000 Forbes Avenue,
Pittsburgh PA, 15221.
Jade Goldstein
Language Technologies Institute,
Carnegie Mellon University,
5000 Forbes Avenue,
Pittsburgh PA, 15221.
Abstract
This paper presents a method for combining query-relevance with
information-novelty in the context of text retrieval and summarization.
The Maximal Marginal Relevance (MMR)
criterion strives to reduce redundancy while
maintaining query relevance in re-ranking
retrieved documents and in selecting
appropriate passages for text summarization.
Preliminary results indicate some benefits for
MMR diversity ranking in document retrieval and in
single document summarization. The latter are
borne out by the recent results of the SUMMAC
conference in the
evaluation of summarization systems.
However, the clearest advantage is demonstrated
in constructing
non-redundant multi-document
summaries, where MMR results are clearly
superior to non-MMR passage selection.
SIGIR'98
24-28 August 1998
Melbourne, Australia.
sigir98@cs.mu.oz.au.