Machine and human performance for single and multidocument summarization

The DUC 2002 evaluation revealed numerous language-processing challenges that impact text summarization. The authors examine the techniques used in a multidocument summarization system they developed and its performance at DUC 2002. They also discuss the need for regularization of human summaries.

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Bibliographic Details
Published in:IEEE intelligent systems 2003-01, Vol.18 (1), p.46-54
Main Authors: Schlesinger, J.D., Conroy, J.M., Okurowski, M.E., O'Leary, D.P.
Format: Article
Language:English
Subjects:
Abstracts
Artificial intelligence
Automatic abstracting
Biographies
Documentation
Evaluation
Guidelines
Hidden Markov models
Human
Human performance
Humans
Information analysis
NIST
Performance analysis
Regularization
Summaries
System performance
Texts
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Description
Summary:The DUC 2002 evaluation revealed numerous language-processing challenges that impact text summarization. The authors examine the techniques used in a multidocument summarization system they developed and its performance at DUC 2002. They also discuss the need for regularization of human summaries.
ISSN:1541-1672
1094-7167
1941-1294
DOI:10.1109/MIS.2003.1179193