Abstract
We aim to automatically generate event-oriented Wikipedia articles by viewing it as a multi-document summarization problem. In this paper, we propose a new model named WikiGen, which consists of two parts: the first one induces a general topic template from existing Wikipedia articles, and the second one generates a summary for each topic by collecting, filtering, and integrating relevant web news, which will be assembled into the full document. Our evaluation results show that WikiGen is capable of generating fluent and comprehensive Wikipedia documents and outperforms previous work, achieving state-of-the-art ROUGE scores.
F. Zhu and Z. Wang—Equal contribution.
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- 1.
\(\alpha = 1.0\) in experiments.
- 2.
\(k = 20\) in experiment.
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Acknowledgement
The work is supported by NSFC key projects (U1736204, 61533018, 61661146007), research fund from State Grid Zhejiang Electric Power Research Institute and THUNUS NExT Co-Lab.
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Zhu, F. et al. (2020). Event-Oriented Wiki Document Generation. In: Wang, X., Lisi, F., Xiao, G., Botoeva, E. (eds) Semantic Technology. JIST 2019. Lecture Notes in Computer Science(), vol 12032. Springer, Cham. https://doi.org/10.1007/978-3-030-41407-8_4
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DOI: https://doi.org/10.1007/978-3-030-41407-8_4
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