The use of MMR, diversity-based reranking for reordering documents and producing summaries
暂无分享,去创建一个
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.
[1] Hans Peter Luhn,et al. The Automatic Creation of Literature Abstracts , 1958, IBM J. Res. Dev..
[2] Chris Buckley,et al. Implementation of the SMART Information Retrieval System , 1985 .
[3] Gerard Salton,et al. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .
[4] Francine Chen,et al. A trainable document summarizer , 1995, SIGIR '95.