| 書目名稱 | Empirical Methods in Natural Language Generation |
| 副標(biāo)題 | Data-oriented Method |
| 編輯 | Emiel Krahmer,Mari?t Theune |
| 視頻video | http://file.papertrans.cn/309/308867/308867.mp4 |
| 概述 | Up to date results.Fast conference proceedings.State-of-the-art report |
| 叢書名稱 | Lecture Notes in Computer Science |
| 圖書封面 |  |
| 描述 | Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research. |
| 出版日期 | Book 2010 |
| 關(guān)鍵詞 | automatic translation; human-human communication; information extraction; information retrieval; knowled |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-15573-4 |
| isbn_softcover | 978-3-642-15572-7 |
| isbn_ebook | 978-3-642-15573-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
| issn_series | 0302-9743 |
| copyright | Springer-Verlag Berlin Heidelberg 2010 |
|Archiver|手機(jī)版|小黑屋|
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