DocumentCode
3530872
Title
A global optimization framework for meeting summarization
Author
Gillick, Dan ; Riedhammer, Korbinian ; Favre, Benoit ; Hakkani-Tür, Dilek
Author_Institution
Comput. Sci. Dept., Univ. of California Berkeley, Berkeley, CA
fYear
2009
fDate
19-24 April 2009
Firstpage
4769
Lastpage
4772
Abstract
We introduce a model for extractive meeting summarization based on the hypothesis that utterances convey bits of information, or concepts. Using keyphrases as concepts weighted by frequency, and an integer linear program to determine the best set of utterances, that is, covering as many concepts as possible while satisfying a length constraint, we achieve ROUGE scores at least as good as a ROUGE-based oracle derived from human summaries. This brings us to a critical discussion of ROUGE and the future of extractive meeting summarization.
Keywords
integer programming; linear programming; text analysis; ROUGE- based oracle; extractive meeting; global optimization framework; human summaries; integer linear program; meeting summarization; Ambient intelligence; Computer science; Data mining; Frequency; Humans; Integer linear programming; integer linear programming; meeting summarization; summarization evaluation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4960697
Filename
4960697
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