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Older versions of the ROUGEeval summarization evaluation system were easier to fool
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
2007 (English)In: Information Processing & Management, ISSN 0306-4573, E-ISSN 1873-5371, Vol. 43, no 6, 1500-1505 p.Article in journal (Refereed) Published
Abstract [en]

We show some limitations of the ROUGE evaluation method for automatic summarization. We present a method for automatic summarization based on a Markov model of the source text. By a simple greedy word selection strategy, summaries with high ROUGE-scores are generated. These summaries would however not be considered good by human readers. The method can be adapted to trick different settings of the ROUGEeval package.

Place, publisher, year, edition, pages
2007. Vol. 43, no 6, 1500-1505 p.
Keyword [en]
automatic summarization, automatic evaluation, Markov models
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-37195DOI: 10.1016/j.ipm.2007.01.014ISI: 000249742500006Scopus ID: 2-s2.0-34547933293OAI: oai:DiVA.org:kth-37195DiVA: diva2:432523
Available from: 2011-08-04 Created: 2011-08-04 Last updated: 2017-12-08Bibliographically approved

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