DocumentCode
2052345
Title
A Metric for Automatically Evaluating Coherent Summaries via Context Chains
Author
Schilder, Frank ; Kondadadi, Ravi
Author_Institution
R&D, Thomson Reuters Corp., St. Paul, MN, USA
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
65
Lastpage
70
Abstract
This paper introduces a new metric for automatically evaluation summaries called ContextChain. Based on an in-depth analysis of the TAC 2008 update summarization results, we show that previous automatic metrics such as ROUGE-2 and BE cannot reliably predict strong performing systems. We introduce two new terms called Correlation Recall and Correlation Precision and discuss how they cast more light on the coverage and the correctness of the respective metric. Our newly proposed metric called ContextChain incorporates findings from Giannakopoulos et al. (2008) and Barzilay and Lapata (2008) [2]. We show that our metric correlates with responsiveness scores even for the top n systems that participated in the TAC 2008 update summarization task, whereas ROUGE-2 and BE do not show a correlation for the top 25 systems.
Keywords
software metrics; text analysis; ContextChain; ROUGE-2; automatic metrics; context chain; correlation precision; correlation recall; in-depth analysis; responsiveness score; update summarization; Delay; Humans; NIST; Organizing; Performance analysis; Sorting; Statistical analysis; Text analysis; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing, 2009. ICSC '09. IEEE International Conference on
Conference_Location
Berkeley, CA
Print_ISBN
978-1-4244-4962-0
Electronic_ISBN
978-0-7695-3800-6
Type
conf
DOI
10.1109/ICSC.2009.100
Filename
5298565
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