Process / pipeline
自然语言生成 — 数据到文本
自然语言生成（NLG）是自然语言处理的一个分支，它能从结构化数据、知识图谱或语义表示中自动生成流畅、人类可读的文本。该方法由 Reiter 和 Dale (2000) 在经典流程中正式提出，并由 Gatt 和 Krahmer (2018) 全面综述，NLG 支持从自动化财务报告和天气预报到数据叙事和对话代理等各种应用。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- 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. link ↗
- Reiter, E. & Dale, R. (2000). Building Natural Language Generation Systems. Cambridge University Press. ISBN: 9780521620369
如何引用本页
ScholarGate. (2026, June 1). Natural Language Generation (NLG). ScholarGate. https://scholargate.app/zh/text-mining/natural-language-generation
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 自动文本评估文本挖掘↔ compare
- GPT模型微调深度学习↔ compare
- 机器翻译文本挖掘↔ compare
- 检索增强生成（RAG）文本挖掘↔ compare
- 序列到序列模型深度学习↔ compare
- 文本摘要文本挖掘↔ compare
- Transformer (NLP)深度学习↔ compare