Ebook Building Natural Language Generation Systems (Studies in Natural Language Processing), by Ehud Reiter, Robert Dale
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Building Natural Language Generation Systems (Studies in Natural Language Processing), by Ehud Reiter, Robert Dale
Ebook Building Natural Language Generation Systems (Studies in Natural Language Processing), by Ehud Reiter, Robert Dale
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This book explains how to build Natural Language Generation (NLG) systems--computer software systems that automatically generate understandable texts in English or other human languages. NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It is essential reading for researchers interested in NLP, AI, and HCI; and for developers interested in advanced document-creation technology.
- Sales Rank: #930619 in Books
- Published on: 2006-03-09
- Original language: English
- Number of items: 1
- Dimensions: 9.02" h x .63" w x 5.98" l, .89 pounds
- Binding: Paperback
- 272 pages
Review
"Consistent and well-developed...a valuable guide..." General Linguistics
"[A]n indispensable guide...extremely well-organized and well-written." User Modeling and User-Adapted Interaction
"Each topic is clearly presented...the information is very well organized...It is detailed, without being too dense or overloaded with technical jargon...This book should be read by anyone interested in natural language processing who wants to get a better idea of the specifics of NLG." Computing Reviews
Most helpful customer reviews
26 of 26 people found the following review helpful.
A worthy introduction to NLG (natural language generation)
By OregonCoast
Summary: Reiter and Dale provide a useful introduction to NLG.
Review: This book is probably the first of its kind. Although there has been considerable work in natural language summarization, research in producing natural language is in its infancy. The authors draw upon actual NLG systems to illustrate the techinical issues involved. They are careful to point out that NLG may not be the best solution for the reader's practical problems. For instance, human writers might produce better text, or mail-merge programs might do the job (albeit with lower quality) at a significantly lower price. A shortcoming -- perhaps a necessary one -- is that the authors hesitate to describe research and development trends for the past decade. The reason does not appear to be a shortage of the quality and quantity of NLG R&D, because the authors do analyze trends for the 1970's and the 1980's. Are the authors hesitant to criticize their contemporary colleagues? A blunt trends analysis would have been helpful, particularly for readers new to the field.
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