Unsupervised Synthesis of Multilingual Wikipedia Articles

In this paper, we propose an unsupervised approach to automatically synthesize Wikipedia articles in multiple languages. Taking an existing high-quality version of any entry as content guideline, we extract keywords from it and use the translated keywords to query the monolingual web of the target language. Candidate excerpts or sentences are selected based on an iterative ranking function and eventually synthesized into a complete article that resembles the reference version closely. 16 English and Chinese articles across 5 domains are evaluated to show that our algorithm is domainindependent. Both subjective evaluations by native Chinese readers and ROUGE-L scores computed with respect to standard reference articles demonstrate that synthesized articles outperform existing Chinese versions or MT texts in both content richness and readability. In practice our method can generate prototype texts for Wikipedia that facilitate later human authoring.

• Type: Journal
• Year: 2010
• Where: COLING
• Authors: Yuncong Chen, Pascale Fung
• Keywords: COLING 2010, Computational Linguistics, Iterative Ranking Function, Native Chinese Readers, Standard Reference Articles