方法证据记录
Natural Language Generation
Natural Language Generation (NLG) is the branch of natural language processing that automatically produces fluent, human-readable text from structured data, knowledge graphs, or semantic representations. Formalised in the classical pipeline by Reiter and Dale (2000) and surveyed comprehensively by Gatt and Krahmer (2018), NLG powers applications ranging from automated financial reporting and weather bulletins to data storytelling and conversational agents.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Natural Language Generation (NLG)
分类方法记录 · process-pipeline / text-mining
- Gatt, A. & Krahmer, E. (2018). Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation. Journal of Artificial Intelligence Research, 61, 65-170. · URL
- Reiter, E. & Dale, R. (2000). Building Natural Language Generation Systems. Cambridge University Press. · ISBN 9780521620369
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