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Automatically Generating Wikipedia Articles: A Structure-Aware Approach

Author(s)
Sauper, Christina Joan; Barzilay, Regina
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Attribution-Noncommercial-Share Alike 3.0 Unported http://creativecommons.org/licenses/by-nc-sa/3.0/
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Abstract
In this paper, we investigate an approach for creating a comprehensive textual overview of a subject composed of information drawn from the Internet. We use the high-level structure of human-authored texts to automatically induce a domain-specific template for the topic structure of a new overview. The algorithmic innovation of our work is a method to learn topic-specific extractors for content selection jointly for the entire template. We augment the standard perceptron algorithm with a global integer linear programming formulation to optimize both local fit of information into each topic and global coherence across the entire overview. The results of our evaluation confirm the benefits of incorporating structural information into the content selection process.
Date issued
2009-08
URI
http://hdl.handle.net/1721.1/58927
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP
Publisher
Association for Computational Linguistics
Citation
Sauper, Christina and Regina Barzilay. "Automatically Generating Wikipedia Articles: A Structure-Aware Approach."Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, pages 208–216, Suntec, Singapore, 2-7 August 2009.
Version: Author's final manuscript
ISBN
978-1-932432-45-9

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